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The field spans layout-aware models, OCR-free vision-language models, and production document extraction services.", "confidence_level": "medium", "confidence_score": 0.83, "source_coverage": { "verified": 3, "total": 3, "ratio": 1 }, "source_count": 3, "source_tiers": [ "A", "B" ], "source_titles": [ "LayoutLM: Pre-training of Text and Layout for Document Image Understanding", "OCR-free Document Understanding Transformer", "Amazon Textract Documentation" ], "claim_count": 3, "claim_ids": [ "https://anchorfact.org/fact/af-ai-document-understanding-1", "https://anchorfact.org/fact/af-ai-document-understanding-2", "https://anchorfact.org/fact/af-ai-document-understanding-3" ], "keywords": [ "document", "understanding", "layout", "ocr", "extraction", "free", "models", "scanned", "structured", "text", "amazon", "image", "images", "information", "layoutlm", "textract", "transformer", "aware", "data", "dimensional", "directly", "documentation", "documented", "documents" ], "search_text": "ai ai document understanding ai document understanding layout parsing structured extraction and intelligent document processing document understanding turns scanned pages forms and pdfs into machine readable structure the field spans layout aware models ocr free vision language models and production document extraction services layoutlm pre training of text and layout for document image understanding ocr free document understanding transformer amazon textract documentation layoutlm jointly models text and two dimensional layout information from scanned document images for document image understanding tasks such as information extraction donut introduced an ocr free document understanding transformer that maps document images directly to structured outputs without a separate ocr engine amazon textract is documented as an ml service for extracting text handwriting and structured data from scanned documents", "routes": { "html": "https://anchorfact.org/ai/ai-document-understanding/", "markdown": "https://anchorfact.org/ai/ai-document-understanding/index.md", "jsonld": "https://anchorfact.org/ai/ai-document-understanding/index.json", "text": "https://anchorfact.org/ai/ai-document-understanding/index.txt", "turtle": "https://anchorfact.org/ai/ai-document-understanding/index.ttl" } }, { "canonical_slug": "ai/ai-drone-autonomy", "title": "AI for Drone Autonomy: Autonomous Navigation, Swarm Coordination, and Aerial Robotics", "url": "https://anchorfact.org/ai/ai-drone-autonomy/", "description": "Drone autonomy uses perception, planning, and control to let aerial robots navigate without continuous human piloting. 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"search_text": "ai ai for algorithmic trading ai for algorithmic trading reinforcement learning market prediction and quantitative finance ai has become the central technology in quantitative finance from reinforcement learning agents that discover optimal trading strategies to nlp models that extract sentiment from earnings calls in milliseconds while hedge funds closely guard their ai systems the underlying techniques deep rl alternative data analysis transformer based time series models are transforming how financial markets operate github ai4finance foundation finrl github ai4finance foundation finrl meta the finrl repository describes finrl as an open source financial reinforcement learning framework the finrl meta repository describes finrl meta as dynamic datasets and market environments for finrl finrl meta positions its data layer and environment layer as shared infrastructure for financial reinforcement learning experiments", "routes": { "html": 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survey nearly doubles the number of known figurative geoglyphs and sheds light on their purpose", "Restoring and attributing ancient texts using deep neural networks", "Students Decipher 2,000-Year-Old Herculaneum Scrolls" ], "claim_count": 3, "claim_ids": [ "https://anchorfact.org/fact/af-ai-for-archaeology-1", "https://anchorfact.org/fact/af-ai-for-archaeology-2", "https://anchorfact.org/fact/af-ai-for-archaeology-3" ], "keywords": [ "archaeology", "restoring", "survey", "ancient", "decipher", "deep", "figurative", "geoglyphs", "herculaneum", "heritage", "inscriptions", "nazca", "neural", "paper", "reported", "scrolls", "site", "text", "000", "2024", "303", "accelerated", "accelerates", "algorithms" ], "search_text": "ai ai for archaeology ai for archaeology site detection artifact classification and digital heritage preservation ai helps archaeology when it accelerates specific expert workflows scanning imagery for site candidates restoring damaged inscriptions and detecting text in otherwise unreadable heritage materials ai accelerated nazca survey nearly doubles the number of known figurative geoglyphs and sheds light on their purpose restoring and attributing ancient texts using deep neural networks students decipher 2 000 year old herculaneum scrolls a 2024 pnas paper reported an ai assisted survey that discovered 303 new figurative geoglyphs in the nazca pampa during a six month field survey the nature paper on ithaca described a deep neural network for restoring missing text and assisting geographic and chronological attribution of ancient greek inscriptions the national endowment for the humanities reported that vesuvius challenge researchers used machine learning algorithms to detect and decipher passages from scans of carbonized herculaneum scrolls", "routes": { "html": "https://anchorfact.org/ai/ai-for-archaeology/", "markdown": "https://anchorfact.org/ai/ai-for-archaeology/index.md", "jsonld": "https://anchorfact.org/ai/ai-for-archaeology/index.json", 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From finding 100+ hidden exoplanets in old NASA data to classifying billions of galaxies, AI is becoming astronomy's most productive tool.", "confidence_level": "high", "confidence_score": 0.85, "source_coverage": { "verified": 2, "total": 2, "ratio": 1 }, "source_count": 2, "source_tiers": [ "A", "S" ], "source_titles": [ "Artificial Intelligence and Statistical Methods in Modern Astrophysics: From Image Processing to Cosmological Discovery", "Training a convolutional neural network for exoplanet classification using transit photometry data" ], "claim_count": 2, "claim_ids": [ "https://anchorfact.org/fact/af-ai-for-astronomy-1", "https://anchorfact.org/fact/af-ai-for-astronomy-2" ], "keywords": [ "data", "astronomy", "classification", "astrophysics", "detection", "exoplanet", "jwst", "100", "2026", "exoplanets", "galaxy", "gravitational", "ligo", "lsst", "methods", "modern", "nasa", "photometry", "process", "rubin", "scientific", "statistical", "transit", "vera" ], "search_text": "ai ai for astronomy ai for astronomy exoplanet detection galaxy classification and computational astrophysics astronomy has become a data driven science drowning in data the vera rubin observatory lsst will generate 20 tb of images per night jwst produces terabytes weekly and ligo streams continuous gravitational wave data ai is the only viable way to process classify and discover in this data deluge from finding 100 hidden exoplanets in old nasa data to classifying billions of galaxies ai is becoming astronomy s most productive tool artificial intelligence and statistical methods in modern astrophysics from image processing to cosmological discovery training a convolutional neural network for exoplanet classification using transit photometry data a comprehensive review fnas journal of scientific innovation march 2026 surveyed ai applications across modern astrophysics covering machine learning for exoplanet detection transit photometry radial velocity galaxy morphology classification hubble sequence jwst deep fields gravitational wave detection ligo virgo glitch classification and transient astronomy real time classification of supernovae gamma ray bursts documenting that cnns now process data from vera rubin lsst jwst and ska telescopes at petabyte scale a university of warwick study sciencedaily may 2026 used a powerful ai pipeline to reanalyze nasa kepler and tess archival data discovering 100 previously undetected exoplanets including 15 rare multi planet systems and several earth sized worlds in habitable zones demonstrating that ai can extract discoveries from already analyzed data that human and traditional statistical methods missed effectively doubling the scientific return of billion dollar space telescope investments", "routes": { "html": "https://anchorfact.org/ai/ai-for-astronomy/", "markdown": "https://anchorfact.org/ai/ai-for-astronomy/index.md", "jsonld": "https://anchorfact.org/ai/ai-for-astronomy/index.json", "text": "https://anchorfact.org/ai/ai-for-astronomy/index.txt", "turtle": "https://anchorfact.org/ai/ai-for-astronomy/index.ttl" } }, { "canonical_slug": "ai/ai-for-audio-processing", "title": "AI for Audio Processing: Sound Event Detection, Acoustic Scene Analysis, and Environmental Intelligence", "url": "https://anchorfact.org/ai/ai-for-audio-processing/", "description": "AI is giving machines the ability to hear and understand their acoustic environment — detecting sirens, recognizing bird species, localizing breaking glass, and monitoring urban noise pollution. 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The most defensible claims are about documented platform capabilities and established SLAM methods, not broad claims about all AR systems being AI-powered.", "confidence_level": "medium", "confidence_score": 0.89, "source_coverage": { "verified": 3, "total": 3, "ratio": 1 }, "source_count": 3, "source_tiers": [ "B", "S" ], "source_titles": [ "Introducing Apple Vision Pro", "ARCore Depth API", "ORB-SLAM3: An Accurate Open-Source Library for Visual, Visual-Inertial, and Multimap SLAM" ], "claim_count": 3, "claim_ids": [ "https://anchorfact.org/fact/af-ai-for-augmented-reality-1", "https://anchorfact.org/fact/af-ai-for-augmented-reality-2", "https://anchorfact.org/fact/af-ai-for-augmented-reality-3" ], "keywords": [ "depth", "visual", "augmented", "reality", "slam", "spatial", "api", "apple", "arcore", "capabilities", "claims", "inertial", "library", "mapping", "multimap", "open", "orb", "pro", "real", "scene", "slam3", "source", "vision", "accurate" ], "search_text": "ai ai for augmented reality ai for augmented reality real time scene understanding spatial computing and contextual overlays ai for augmented reality is grounded in scene sensing depth estimation tracking and spatial mapping the most defensible claims are about documented platform capabilities and established slam methods not broad claims about all ar systems being ai powered introducing apple vision pro arcore depth api orb slam3 an accurate open source library for visual visual inertial and multimap slam apple introduced vision pro as a spatial computer using an r1 chip to process input from 12 cameras five sensors and six microphones google documents the arcore depth api as producing depth maps that let ar apps support capabilities such as occlusion and interaction with real world surfaces orb slam3 is described as an open source slam library supporting visual visual inertial and multimap simultaneous localization and mapping", "routes": { "html": "https://anchorfact.org/ai/ai-for-augmented-reality/", "markdown": "https://anchorfact.org/ai/ai-for-augmented-reality/index.md", "jsonld": "https://anchorfact.org/ai/ai-for-augmented-reality/index.json", "text": "https://anchorfact.org/ai/ai-for-augmented-reality/index.txt", "turtle": "https://anchorfact.org/ai/ai-for-augmented-reality/index.ttl" } }, { "canonical_slug": "ai/ai-for-augmented-reality-real-time-object-detection-depth-estimation-and-scene-understanding", "title": "AI for Augmented Reality: Real-Time Object Detection, Depth Estimation, and Scene Understanding", "url": "https://anchorfact.org/ai/ai-for-augmented-reality-real-time-object-detection-depth-estimation-and-scene-understanding/", "description": "AI for AR combines tracking, anchors, depth maps, object detection, segmentation, and scene understanding. For agents building game or XR prototypes, the important operational boundary is that AR output must be checked against real device support, latency, lighting, and user safety constraints.", "confidence_level": "medium", "confidence_score": 0.83, "source_coverage": { "verified": 5, "total": 5, "ratio": 1 }, "source_count": 5, "source_tiers": [ "A", "B" ], "source_titles": [ "ARCore Depth API", "Working with anchors", "MediaPipe Object Detector", "Segment Anything", "Towards Robust Monocular Depth Estimation: Mixing Datasets for Zero-shot Cross-dataset Transfer" ], "claim_count": 5, "claim_ids": [ "https://anchorfact.org/fact/af-ai-ar-1", "https://anchorfact.org/fact/af-ai-ar-2", "https://anchorfact.org/fact/af-ai-ar-3", "https://anchorfact.org/fact/af-ai-ar-4", "https://anchorfact.org/fact/af-ai-ar-5" ], "keywords": [ "depth", "object", "real", "estimation", "anchors", "arcore", "dataset", "detection", "device", "scene", "understanding", "anything", "api", "augmented", "building", "datasets", "detector", "image", "maps", "mediapipe", "mixing", "monocular", "objects", "reality" ], "search_text": "ai ai for augmented reality real time object detection depth estimation and scene understanding ai for augmented reality real time object detection depth estimation and scene understanding ai for ar combines tracking anchors depth maps object detection segmentation and scene understanding for agents building game or xr prototypes the important operational boundary is that ar output must be checked against real device support latency lighting and user safety constraints arcore depth api working with anchors mediapipe object detector segment anything towards robust monocular depth estimation mixing datasets for zero shot cross dataset transfer arcore s depth api uses a supported device camera to create depth maps allowing virtual objects to interact with real world geometry more plausibly arcore anchors attach virtual content to trackable real world positions so that placed objects can remain stable as device tracking updates mediapipe s object detector task identifies object classes and locations in image or video input making it a practical building block for ar overlays segment anything introduced a promptable segmentation model and the sa 1b dataset for producing object masks from points boxes or other prompts midas style monocular depth work shows that robust single image depth estimation depends on mixing datasets and training objectives rather than relying on one narrow dataset", "routes": { "html": "https://anchorfact.org/ai/ai-for-augmented-reality-real-time-object-detection-depth-estimation-and-scene-understanding/", "markdown": "https://anchorfact.org/ai/ai-for-augmented-reality-real-time-object-detection-depth-estimation-and-scene-understanding/index.md", "jsonld": "https://anchorfact.org/ai/ai-for-augmented-reality-real-time-object-detection-depth-estimation-and-scene-understanding/index.json", "text": "https://anchorfact.org/ai/ai-for-augmented-reality-real-time-object-detection-depth-estimation-and-scene-understanding/index.txt", "turtle": "https://anchorfact.org/ai/ai-for-augmented-reality-real-time-object-detection-depth-estimation-and-scene-understanding/index.ttl" } }, { "canonical_slug": "ai/ai-for-chemistry", "title": "AI for Chemistry: Reaction Prediction, Retrosynthesis, and Computational Chemistry", "url": "https://anchorfact.org/ai/ai-for-chemistry/", "description": "AI methods are useful in chemistry when they are tied to clear chemical representations and experimentally or computationally checked outputs. Current public evidence is strongest for bounded examples such as equivariant neural-network potentials, sequence-to-sequence reaction prediction, and deep-learning screens for candidate molecules.", "confidence_level": "medium", "confidence_score": 0.86, "source_coverage": { "verified": 3, "total": 3, "ratio": 1 }, "source_count": 3, "source_tiers": [ "S" ], "source_titles": [ "E(3)-equivariant graph neural networks for data-efficient and accurate interatomic potentials", "Molecular Transformer: A Model for Uncertainty-Calibrated Chemical Reaction Prediction", "A Deep Learning Approach to Antibiotic Discovery" ], "claim_count": 3, "claim_ids": [ "https://anchorfact.org/fact/af-ai-for-chemistry-1", "https://anchorfact.org/fact/af-ai-for-chemistry-2", "https://anchorfact.org/fact/af-ai-for-chemistry-3" ], "keywords": [ "chemistry", "learning", "molecular", "prediction", "reaction", "sequence", "approach", "chemical", "deep", "equivariant", "neural", "potentials", "calibrated", "candidate", "data", "graph", "interatomic", "molecules", "network", "reports", "representations", "transformer", "uncertainty", "accuracy" ], "search_text": "ai ai for chemistry ai for chemistry reaction prediction retrosynthesis and computational chemistry ai methods are useful in chemistry when they are tied to clear chemical representations and experimentally or computationally checked outputs current public evidence is strongest for bounded examples such as equivariant neural network potentials sequence to sequence reaction prediction and deep learning screens for candidate molecules e 3 equivariant graph neural networks for data efficient and accurate interatomic potentials molecular transformer a model for uncertainty calibrated chemical reaction prediction a deep learning approach to antibiotic discovery nequip is an e 3 equivariant graph neural network approach for learning interatomic potentials from ab initio reference calculations and its nature communications paper reports strong accuracy and data efficiency on molecular and materials benchmarks the molecular transformer frames chemical reaction prediction as a sequence to sequence task over molecular representations and reports uncertainty calibrated product predictions in acs central science stokes et al used a deep learning workflow to screen molecules for antibacterial activity and reported halicin as a candidate identified by that approach", "routes": { "html": "https://anchorfact.org/ai/ai-for-chemistry/", "markdown": "https://anchorfact.org/ai/ai-for-chemistry/index.md", "jsonld": "https://anchorfact.org/ai/ai-for-chemistry/index.json", "text": "https://anchorfact.org/ai/ai-for-chemistry/index.txt", "turtle": "https://anchorfact.org/ai/ai-for-chemistry/index.ttl" } }, { "canonical_slug": "ai/ai-for-chip-design", "title": "AI for Chip Design: Reinforcement Learning Placement, EDA Automation, and Semiconductor Intelligence", "url": "https://anchorfact.org/ai/ai-for-chip-design/", "description": "AI for chip design covers specific electronic-design-automation tasks such as floorplanning, placement, and computational lithography. Public claims should stay tied to individual methods and systems rather than saying AI can automate an entire chip tapeout.", "confidence_level": "medium", "confidence_score": 0.89, "source_coverage": { "verified": 3, "total": 3, "ratio": 1 }, "source_count": 3, "source_tiers": [ "A", "B", "S" ], "source_titles": [ "A graph placement methodology for fast chip design", "DREAMPlace: Deep Learning Toolkit-Enabled GPU Acceleration for Modern VLSI Placement", "NVIDIA cuLitho" ], "claim_count": 3, "claim_ids": [ "https://anchorfact.org/fact/af-ai-for-chip-design-1", "https://anchorfact.org/fact/af-ai-for-chip-design-2", "https://anchorfact.org/fact/af-ai-for-chip-design-3" ], "keywords": [ "chip", "placement", "design", "learning", "acceleration", "automation", "computational", "culitho", "deep", "dreamplace", "floorplanning", "gpu", "graph", "lithography", "nvidia", "reinforcement", "semiconductor", "toolkit", "vlsi", "accelerating", "automate", "claims", "covers", "describes" ], "search_text": "ai ai for chip design ai for chip design reinforcement learning placement eda automation and semiconductor intelligence ai for chip design covers specific electronic design automation tasks such as floorplanning placement and computational lithography public claims should stay tied to individual methods and systems rather than saying ai can automate an entire chip tapeout a graph placement methodology for fast chip design dreamplace deep learning toolkit enabled gpu acceleration for modern vlsi placement nvidia culitho the nature chip placement paper framed floorplanning as a reinforcement learning problem over graph structured chip netlists dreamplace formulated vlsi placement in a way that uses deep learning toolkit infrastructure and gpu acceleration for global placement nvidia describes culitho as a computational lithography library for accelerating semiconductor manufacturing workloads on gpus", "routes": { "html": "https://anchorfact.org/ai/ai-for-chip-design/", "markdown": "https://anchorfact.org/ai/ai-for-chip-design/index.md", "jsonld": "https://anchorfact.org/ai/ai-for-chip-design/index.json", "text": "https://anchorfact.org/ai/ai-for-chip-design/index.txt", "turtle": "https://anchorfact.org/ai/ai-for-chip-design/index.ttl" } }, { "canonical_slug": "ai/ai-for-climate-science", "title": "AI for Climate Science: Weather Prediction and Earth System Modeling", "url": "https://anchorfact.org/ai/ai-for-climate-science/", "description": "AI for climate and weather science is strongest when described as a set of specific learned forecasting and simulation methods. Public claims should distinguish weather forecasting, climate simulation, and operational climate-risk analysis.", "confidence_level": "medium", "confidence_score": 0.88, "source_coverage": { "verified": 3, "total": 3, "ratio": 1 }, "source_count": 3, "source_tiers": [ "A", "S" ], "source_titles": [ "Learning skillful medium-range global weather forecasting", "FourCastNet: A Global Data-driven High-resolution Weather Model using Adaptive Fourier Neural Operators", "Neural general circulation models for weather and climate" ], "claim_count": 3, "claim_ids": [ "https://anchorfact.org/fact/af-ai-for-climate-science-1", "https://anchorfact.org/fact/af-ai-for-climate-science-2", "https://anchorfact.org/fact/af-ai-for-climate-science-3" ], "keywords": [ "weather", "climate", "forecasting", "global", "neural", "described", "science", "simulation", "adaptive", "circulation", "data", "driven", "fourcastnet", "fourier", "general", "high", "learned", "medium", "model", "models", "operators", "paper", "range", "resolution" ], "search_text": "ai ai for climate science ai for climate science weather prediction and earth system modeling ai for climate and weather science is strongest when described as a set of specific learned forecasting and simulation methods public claims should distinguish weather forecasting climate simulation and operational climate risk analysis learning skillful medium range global weather forecasting fourcastnet a global data driven high resolution weather model using adaptive fourier neural operators neural general circulation models for weather and climate the graphcast paper presented a learned global weather forecasting system for medium range forecasts fourcastnet described a data driven high resolution global weather model based on adaptive fourier neural operators the neuralgcm paper described hybrid neural general circulation models for weather forecasting and climate simulation", "routes": { "html": "https://anchorfact.org/ai/ai-for-climate-science/", "markdown": "https://anchorfact.org/ai/ai-for-climate-science/index.md", "jsonld": "https://anchorfact.org/ai/ai-for-climate-science/index.json", "text": "https://anchorfact.org/ai/ai-for-climate-science/index.txt", "turtle": "https://anchorfact.org/ai/ai-for-climate-science/index.ttl" } }, { "canonical_slug": "ai/ai-for-code-generation", "title": "AI for Code Generation: LLMs as Software Engineering Copilots", "url": "https://anchorfact.org/ai/ai-for-code-generation/", "description": "AI code generation has evolved from simple line-level autocomplete to models that can understand entire codebases, fix bugs in production systems, and implement multi-file features from natural language descriptions. LLMs like GitHub Copilot, Claude Code, and Cursor are transforming software engineering by serving as always-available pair programmers.", "confidence_level": "high", "confidence_score": 0.85, "source_coverage": { "verified": 2, "total": 2, "ratio": 1 }, "source_count": 2, "source_tiers": [ "A", "S" ], "source_titles": [ "A Survey on Large Language Models for Code Generation", "SWE-bench: Can Language Models Resolve Real-World GitHub Issues?" ], "claim_count": 2, "claim_ids": [ "https://anchorfact.org/fact/af-ai-for-code-generation-1", "https://anchorfact.org/fact/af-ai-for-code-generation-2" ], "keywords": [ "code", "generation", "models", "language", "bench", "engineering", "software", "swe", "2026", "agents", "github", "large", "like", "llms", "real", "survey", "world", "2024", "2025", "achieve", "achieved", "acm", "always", "approaches" ], "search_text": "ai ai for code generation ai for code generation llms as software engineering copilots ai code generation has evolved from simple line level autocomplete to models that can understand entire codebases fix bugs in production systems and implement multi file features from natural language descriptions llms like github copilot claude code and cursor are transforming software engineering by serving as always available pair programmers a survey on large language models for code generation swe bench can language models resolve real world github issues acm january 2026 published a comprehensive survey on large language models for code generation documenting that gpt 4 achieved 88 4 on humaneval while open source models like deepseek coder v2 reached 90 2 on the same benchmark in 2025 swe bench princeton 2024 has become the de facto standard for evaluating ai coding agents on real world software engineering tasks as of early 2026 the best agents achieve 40 50 resolution rate on swe bench verified compared to 1 2 for naive llm approaches", "routes": { "html": "https://anchorfact.org/ai/ai-for-code-generation/", "markdown": "https://anchorfact.org/ai/ai-for-code-generation/index.md", "jsonld": "https://anchorfact.org/ai/ai-for-code-generation/index.json", "text": "https://anchorfact.org/ai/ai-for-code-generation/index.txt", "turtle": "https://anchorfact.org/ai/ai-for-code-generation/index.ttl" } }, { "canonical_slug": "ai/ai-for-complex-networks", "title": "AI for Complex Networks: Graph Learning, Resilience, and Network Science", "url": "https://anchorfact.org/ai/ai-for-complex-networks/", "description": "AI for complex networks uses graph representations to model relationships among entities. Strong public claims should stay close to graph neural network papers and graph-analysis tooling.", "confidence_level": "medium", "confidence_score": 0.83, "source_coverage": { "verified": 3, "total": 3, "ratio": 1 }, "source_count": 3, "source_tiers": [ "A", "B" ], "source_titles": [ "Semi-Supervised Classification with Graph Convolutional Networks", "Graph Attention Networks", "NetworkX Algorithms" ], "claim_count": 3, "claim_ids": [ "https://anchorfact.org/fact/af-ai-for-complex-networks-1", "https://anchorfact.org/fact/af-ai-for-complex-networks-2", "https://anchorfact.org/fact/af-ai-for-complex-networks-3" ], "keywords": [ "graph", "networks", "analysis", "complex", "algorithms", "attention", "convolutional", "data", "learning", "network", "networkx", "neural", "semi", "structured", "supervised", "among", "attentional", "centrality", "claims", "classification", "close", "community", "connectivity", "directly" ], "search_text": "ai ai for complex networks ai for complex networks graph learning resilience and network science ai for complex networks uses graph representations to model relationships among entities strong public claims should stay close to graph neural network papers and graph analysis tooling semi supervised classification with graph convolutional networks graph attention networks networkx algorithms kipf and welling presented graph convolutional networks for semi supervised learning directly on graph structured data graph attention networks introduced masked self attentional layers for neural processing of graph structured data networkx documents algorithms for graph analysis tasks including link analysis shortest paths centrality connectivity and community analysis", "routes": { "html": "https://anchorfact.org/ai/ai-for-complex-networks/", "markdown": "https://anchorfact.org/ai/ai-for-complex-networks/index.md", "jsonld": "https://anchorfact.org/ai/ai-for-complex-networks/index.json", "text": "https://anchorfact.org/ai/ai-for-complex-networks/index.txt", "turtle": "https://anchorfact.org/ai/ai-for-complex-networks/index.ttl" } }, { "canonical_slug": "ai/ai-for-construction", "title": "AI for Construction: Computer Vision Safety, BIM Digital Twins, and Automated Project Monitoring", "url": "https://anchorfact.org/ai/ai-for-construction/", "description": "AI for construction supports site monitoring, inspection, schedule awareness, and model comparison. The reliable public framing is not \"AI reduces accidents by a fixed percentage\"; it is that computer vision and BIM-linked workflows are active research and deployment areas with clear site-specific constraints.", "confidence_level": "medium", "confidence_score": 0.84, "source_coverage": { "verified": 3, "total": 3, "ratio": 1 }, "source_count": 3, "source_tiers": [ "S" ], "source_titles": [ "Artificial Intelligence and Smart Vision for Building and Construction 4.0: Machine and Deep Learning Methods and Applications", "Computer Vision Applications in Construction: Current State, Opportunities and Challenges", "Automated Computer Vision-Based Construction Progress Monitoring: A Systematic Review" ], "claim_count": 3, "claim_ids": [ "https://anchorfact.org/fact/af-ai-for-construction-1", "https://anchorfact.org/fact/af-ai-for-construction-2", "https://anchorfact.org/fact/af-ai-for-construction-3" ], "keywords": [ "construction", "vision", "computer", "monitoring", "site", "applications", "progress", "automated", "bim", "inspection", "research", "review", "smart", "accidents", "across", "active", "analysis", "areas", "artificial", "awareness", "based", "been", "building", "built" ], "search_text": "ai ai for construction ai for construction computer vision safety bim digital twins and automated project monitoring ai for construction supports site monitoring inspection schedule awareness and model comparison the reliable public framing is not ai reduces accidents by a fixed percentage it is that computer vision and bim linked workflows are active research and deployment areas with clear site specific constraints artificial intelligence and smart vision for building and construction 4 0 machine and deep learning methods and applications computer vision applications in construction current state opportunities and challenges automated computer vision based construction progress monitoring a systematic review a review of ai and smart vision in construction describes applications across monitoring inspection and site decision support computer vision has been reviewed as a construction technology for site monitoring object detection and progress analysis computer vision progress monitoring research uses site images and 3d data to compare as built construction status with planned work", "routes": { "html": "https://anchorfact.org/ai/ai-for-construction/", "markdown": "https://anchorfact.org/ai/ai-for-construction/index.md", "jsonld": "https://anchorfact.org/ai/ai-for-construction/index.json", "text": "https://anchorfact.org/ai/ai-for-construction/index.txt", "turtle": "https://anchorfact.org/ai/ai-for-construction/index.ttl" } }, { "canonical_slug": "ai/ai-for-cultural-heritage", "title": "AI for Cultural Heritage: Digital Preservation, Art Attribution, and Museum Intelligence", "url": "https://anchorfact.org/ai/ai-for-cultural-heritage/", "description": "AI and adjacent computational tools support cultural heritage through text restoration, scroll reading, and high-resolution digitization. These systems assist experts; they do not replace provenance work, conservation judgment, or historical interpretation.", "confidence_level": "medium", "confidence_score": 0.89, "source_coverage": { "verified": 3, "total": 3, "ratio": 1 }, "source_count": 3, "source_tiers": [ "B", "S" ], "source_titles": [ "Restoring and attributing ancient texts using deep neural networks", "Students Decipher 2,000-Year-Old Herculaneum Scrolls", "Art Camera" ], "claim_count": 3, "claim_ids": [ "https://anchorfact.org/fact/af-ai-for-cultural-heritage-1", "https://anchorfact.org/fact/af-ai-for-cultural-heritage-2", "https://anchorfact.org/fact/af-ai-for-cultural-heritage-3" ], "keywords": [ "art", "cultural", "heritage", "ancient", "attribution", "camera", "deep", "digital", "herculaneum", "high", "neural", "resolution", "restoring", "scrolls", "text", "000", "adjacent", "arts", "artworks", "assist", "assisting", "attributing", "carbonized", "challenge" ], "search_text": "ai ai for cultural heritage ai for cultural heritage digital preservation art attribution and museum intelligence ai and adjacent computational tools support cultural heritage through text restoration scroll reading and high resolution digitization these systems assist experts they do not replace provenance work conservation judgment or historical interpretation restoring and attributing ancient texts using deep neural networks students decipher 2 000 year old herculaneum scrolls art camera the ithaca nature paper presented a deep neural network for restoring missing text and assisting geographic and chronological attribution of ancient greek inscriptions the national endowment for the humanities reported that vesuvius challenge researchers used machine learning methods to read passages from carbonized herculaneum scrolls google arts culture describes art camera as a system for creating ultra high resolution images of artworks for digital viewing and study", "routes": { "html": "https://anchorfact.org/ai/ai-for-cultural-heritage/", "markdown": "https://anchorfact.org/ai/ai-for-cultural-heritage/index.md", "jsonld": "https://anchorfact.org/ai/ai-for-cultural-heritage/index.json", "text": "https://anchorfact.org/ai/ai-for-cultural-heritage/index.txt", "turtle": "https://anchorfact.org/ai/ai-for-cultural-heritage/index.ttl" } }, { "canonical_slug": "ai/ai-for-data-curation", "title": "AI for Data Curation: Web-Scale Filtering, Deduplication, and Quality Scoring for LLM Training", "url": "https://anchorfact.org/ai/ai-for-data-curation/", "description": "Data curation is the unglamorous workhorse behind every great LLM -- transforming petabytes of noisy web crawl data into clean, deduplicated, high-quality training corpora. 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"search_text": "ai ai for visualization ai for data visualization ai for visualization includes machine learning methods that help project high dimensional data recommend charts or support exploratory analysis the safest public claims focus on specific techniques such as t sne umap and learned visualization recommendation visualizing data using t sne umap uniform manifold approximation and projection for dimension reduction vizml a machine learning approach to visualization recommendation t sne was introduced as a nonlinear dimensionality reduction method for visualizing high dimensional data in two or three dimensions umap was proposed as a manifold learning technique for dimension reduction and visualization vizml frames visualization recommendation as a machine learning problem trained from a large corpus of dataset visualization pairs", "routes": { "html": "https://anchorfact.org/ai/ai-for-visualization/", "markdown": "https://anchorfact.org/ai/ai-for-visualization/index.md", 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learning skillful medium range global weather forecasting accurate medium range global weather forecasting with 3d neural networks fourcastnet a global data driven high resolution weather model using adaptive fourier neural operators graphcast presents a machine learning system for skillful medium range global weather forecasting pangu weather uses 3d neural networks for medium range global weather forecasting fourcastnet applies adaptive fourier neural operators to global high resolution data driven weather modeling", "routes": { "html": "https://anchorfact.org/ai/ai-for-weather-forecasting/", "markdown": "https://anchorfact.org/ai/ai-for-weather-forecasting/index.md", "jsonld": "https://anchorfact.org/ai/ai-for-weather-forecasting/index.json", "text": "https://anchorfact.org/ai/ai-for-weather-forecasting/index.txt", "turtle": "https://anchorfact.org/ai/ai-for-weather-forecasting/index.ttl" } }, { "canonical_slug": "ai/ai-for-wildlife-conservation", "title": "AI for Wildlife 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survey frames the field around deep learning on structured domains such as graphs groups and manifolds graph convolutional networks apply neural network layers to graph structured data for semi supervised classification pointnet directly processes point sets for 3d classification and segmentation tasks", "routes": { "html": "https://anchorfact.org/ai/geometric-deep-learning/", "markdown": "https://anchorfact.org/ai/geometric-deep-learning/index.md", "jsonld": "https://anchorfact.org/ai/geometric-deep-learning/index.json", "text": "https://anchorfact.org/ai/geometric-deep-learning/index.txt", "turtle": "https://anchorfact.org/ai/geometric-deep-learning/index.ttl" } }, { "canonical_slug": "ai/gpt-models", "title": "GPT (Generative Pre-trained Transformer) Model Family", "url": "https://anchorfact.org/ai/gpt-models/", "description": "The GPT (Generative Pre-trained Transformer) model family, developed by OpenAI starting in 2018, represents the lineage of autoregressive language models 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Strong public claims should stay tied to datasets, semantic parsing methods, and decoding constraints.", "confidence_level": "medium", "confidence_score": 0.8, "source_coverage": { "verified": 3, "total": 3, "ratio": 1 }, "source_count": 3, "source_tiers": [ "A" ], "source_titles": [ "Seq2SQL: Generating Structured Queries from Natural Language using Reinforcement Learning", "Spider: A Large-Scale Human-Labeled Dataset for Complex and Cross-Domain Semantic Parsing and Text-to-SQL Task", "PICARD: Parsing Incrementally for Constrained Auto-Regressive Decoding from Language Models" ], "claim_count": 3, "claim_ids": [ "https://anchorfact.org/fact/af-text-to-sql-1", "https://anchorfact.org/fact/af-text-to-sql-2", "https://anchorfact.org/fact/af-text-to-sql-3" ], "keywords": [ "sql", "language", "parsing", "text", "natural", "database", "decoding", "queries", "semantic", "auto", "cross", "dataset", "domain", "generating", "incrementally", "large", "learning", "models", "picard", "regressive", "reinforcement", "seq2sql", "spider", "claims" ], "search_text": "ai text to sql text to sql natural language database querying with large language models text to sql converts natural language questions into database queries strong public claims should stay tied to datasets semantic parsing methods and decoding constraints seq2sql generating structured queries from natural language using reinforcement learning spider a large scale human labeled dataset for complex and cross domain semantic parsing and text to sql task picard parsing incrementally for constrained auto regressive decoding from language models seq2sql studied generating sql queries from natural language and used reinforcement learning to optimize unordered query components spider is a cross domain semantic parsing and text to sql dataset designed to test generalization to unseen database schemas picard constrains auto regressive decoding by incrementally parsing generated sql and rejecting invalid continuations", "routes": { "html": "https://anchorfact.org/ai/text-to-sql/", "markdown": "https://anchorfact.org/ai/text-to-sql/index.md", "jsonld": "https://anchorfact.org/ai/text-to-sql/index.json", "text": "https://anchorfact.org/ai/text-to-sql/index.txt", "turtle": "https://anchorfact.org/ai/text-to-sql/index.ttl" } }, { "canonical_slug": "ai/time-series-forecasting", "title": "Time Series Forecasting with Machine Learning", "url": "https://anchorfact.org/ai/time-series-forecasting/", "description": "Time-series forecasting is relevant to AI agents that plan capacity, monitor metrics, predict demand, or schedule content production. 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vocabulary oov problem character level tiny vocabulary long sequences subword balanced bpe wordpiece sentencepiece standard for modern llms subword tokenization handles rare and unseen words by decomposing into known subword units bert uses wordpiece tokenization for its input representation sentencepiece t5 llama treats input as raw text language agnostic no pre tokenization", "routes": { "html": "https://anchorfact.org/ai/tokenization-in-nlp/", "markdown": "https://anchorfact.org/ai/tokenization-in-nlp/index.md", "jsonld": "https://anchorfact.org/ai/tokenization-in-nlp/index.json", "text": "https://anchorfact.org/ai/tokenization-in-nlp/index.txt", "turtle": "https://anchorfact.org/ai/tokenization-in-nlp/index.ttl" } }, { "canonical_slug": "ai/tool-call-streaming-and-incremental-results", "title": "Tool Call Streaming and Incremental Results", "url": "https://anchorfact.org/ai/tool-call-streaming-and-incremental-results/", "description": "Tool-call streaming lets an agent expose 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index parameters and recall latency tuning vector index parameters and recall latency tuning vector index settings are production knobs agents should not change them without measuring recall latency memory and filtered search behavior on the actual query mix weaviate vector index pinecone create index qdrant indexing weaviate documentation says hnsw ef balances search speed and recall with higher ef improving accuracy while slowing search pinecone create index documentation includes dimension and metric fields for configuring a dense vector index qdrant documentation says vector indexes speed up vector search and payload indexes speed up filtering", "routes": { "html": "https://anchorfact.org/ai/vector-index-parameters-and-recall-latency-tuning/", "markdown": "https://anchorfact.org/ai/vector-index-parameters-and-recall-latency-tuning/index.md", "jsonld": "https://anchorfact.org/ai/vector-index-parameters-and-recall-latency-tuning/index.json", "text": 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compilation database as recording compile options for source files in a project cmake documentation says cmake export compile commands generates a compile commands json file containing exact compiler calls for all translation units clangd documentation says a compilation database can be a compile commands json file that lists commands for each file", "routes": { "html": "https://anchorfact.org/computer-science/code-compile-commands-and-language-toolchains/", "markdown": "https://anchorfact.org/computer-science/code-compile-commands-and-language-toolchains/index.md", "jsonld": "https://anchorfact.org/computer-science/code-compile-commands-and-language-toolchains/index.json", "text": "https://anchorfact.org/computer-science/code-compile-commands-and-language-toolchains/index.txt", "turtle": "https://anchorfact.org/computer-science/code-compile-commands-and-language-toolchains/index.ttl" } }, { "canonical_slug": "computer-science/code-ctags-symbol-indexes-for-repository-agents", "title": "Code ctags Symbol Indexes for Repository Agents", "url": "https://anchorfact.org/computer-science/code-ctags-symbol-indexes-for-repository-agents/", "description": "ctags files give repository agents a lightweight symbol index for jumping from names to definitions across many languages.", "confidence_level": "medium", "confidence_score": 0.685, "source_coverage": { "verified": 2, "total": 2, "ratio": 1 }, "source_count": 2, "source_tiers": [ "B" ], "source_titles": [ "Universal Ctags Manual", "Universal Ctags Output Formats" ], "claim_count": 3, "claim_ids": [ "https://anchorfact.org/fact/fact-cs-code-ctags-symbol-indexes-for-repository-agents-1", "https://anchorfact.org/fact/fact-cs-code-ctags-symbol-indexes-for-repository-agents-2", "https://anchorfact.org/fact/fact-cs-code-ctags-symbol-indexes-for-repository-agents-3" ], "keywords": [ "ctags", "universal", "files", "agents", "code", "documentation", "repository", "symbol", "describes", "formats", "index", "indexes", "output", "source", "tag", "across", "client", "computer", "definitions", "editors", "etags", "found", "generating", "give" ], "search_text": "computer science code ctags symbol indexes for repository agents code ctags symbol indexes for repository agents ctags files give repository agents a lightweight symbol index for jumping from names to definitions across many languages universal ctags manual universal ctags output formats universal ctags documentation describes ctags as generating tag files for source code universal ctags documentation says tag files index language objects found in source files so editors or client tools can quickly locate them universal ctags documentation describes output formats including u ctags e ctags etags xref and json", "routes": { "html": "https://anchorfact.org/computer-science/code-ctags-symbol-indexes-for-repository-agents/", "markdown": "https://anchorfact.org/computer-science/code-ctags-symbol-indexes-for-repository-agents/index.md", "jsonld": 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communication between development tools and debuggers the debug adapter protocol specification defines protocol messages including requests responses and events the debug adapter protocol repository publishes a json schema for protocol messages", "routes": { "html": "https://anchorfact.org/computer-science/code-debug-adapter-protocol-for-agents/", "markdown": "https://anchorfact.org/computer-science/code-debug-adapter-protocol-for-agents/index.md", "jsonld": "https://anchorfact.org/computer-science/code-debug-adapter-protocol-for-agents/index.json", "text": "https://anchorfact.org/computer-science/code-debug-adapter-protocol-for-agents/index.txt", "turtle": "https://anchorfact.org/computer-science/code-debug-adapter-protocol-for-agents/index.ttl" } }, { "canonical_slug": "computer-science/code-dependency-graphs-and-vulnerability-advisories", "title": "Code Dependency Graphs and Vulnerability Advisories", "url": "https://anchorfact.org/computer-science/code-dependency-graphs-and-vulnerability-advisories/", "description": "Dependency graphs and vulnerability advisories help agents connect package manifests to known security risk and upgrade paths.", "confidence_level": "medium", "confidence_score": 0.725, "source_coverage": { "verified": 3, "total": 3, "ratio": 1 }, "source_count": 3, "source_tiers": [ "B" ], "source_titles": [ "deps.dev API", "npm audit", "OSV Query API" ], "claim_count": 3, "claim_ids": [ "https://anchorfact.org/fact/fact-cs-code-dependency-graphs-and-vulnerability-advisories-1", "https://anchorfact.org/fact/fact-cs-code-dependency-graphs-and-vulnerability-advisories-2", "https://anchorfact.org/fact/fact-cs-code-dependency-graphs-and-vulnerability-advisories-3" ], "keywords": [ "api", "dependency", "advisories", "describes", "documentation", "graphs", "npm", "vulnerability", "audit", "code", "deps", "dev", "known", "osv", "package", "query", "vulnerabilities", "accessing", "agents", "computer", "connect", "data", "description", "endpoint" ], "search_text": "computer science code dependency graphs and vulnerability advisories code dependency graphs and vulnerability advisories dependency graphs and vulnerability advisories help agents connect package manifests to known security risk and upgrade paths deps dev api npm audit osv query api the deps dev api documentation describes an api for accessing open source insights data npm documentation describes npm audit as submitting a dependency description and returning a report of known vulnerabilities osv api documentation describes the post v1 query endpoint for querying vulnerabilities for a package", "routes": { "html": "https://anchorfact.org/computer-science/code-dependency-graphs-and-vulnerability-advisories/", "markdown": "https://anchorfact.org/computer-science/code-dependency-graphs-and-vulnerability-advisories/index.md", "jsonld": 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used with linguist vendored to mark vendored files git documentation says gitattributes files define attributes for pathnames", "routes": { "html": "https://anchorfact.org/computer-science/code-generated-files-and-vendored-code-detection/", "markdown": "https://anchorfact.org/computer-science/code-generated-files-and-vendored-code-detection/index.md", "jsonld": "https://anchorfact.org/computer-science/code-generated-files-and-vendored-code-detection/index.json", "text": "https://anchorfact.org/computer-science/code-generated-files-and-vendored-code-detection/index.txt", "turtle": "https://anchorfact.org/computer-science/code-generated-files-and-vendored-code-detection/index.ttl" } }, { "canonical_slug": "computer-science/code-git-blame-and-commit-history-for-agents", "title": "Code Git Blame and Commit History for Agents", "url": "https://anchorfact.org/computer-science/code-git-blame-and-commit-history-for-agents/", "description": "Git blame and commit history help agents understand why code changed before proposing edits or assigning ownership.", "confidence_level": "medium", "confidence_score": 0.725, "source_coverage": { "verified": 3, "total": 3, "ratio": 1 }, "source_count": 3, "source_tiers": [ "B" ], "source_titles": [ "Git Blame Documentation", "Git Log Documentation", "Git Rev-List Documentation" ], "claim_count": 3, "claim_ids": [ "https://anchorfact.org/fact/fact-cs-code-git-blame-and-commit-history-for-agents-1", "https://anchorfact.org/fact/fact-cs-code-git-blame-and-commit-history-for-agents-2", "https://anchorfact.org/fact/fact-cs-code-git-blame-and-commit-history-for-agents-3" ], "keywords": [ "git", "documentation", "blame", "commit", "agents", "code", "describes", "history", "list", "log", "rev", "showing", "assigning", "author", "before", "changed", "chronological", "computer", "default", "each", "edits", "file", "help", "last" ], "search_text": "computer science code git blame and commit history for agents code git blame and commit history for agents git blame and commit history help agents understand why code changed before proposing edits or assigning ownership git blame documentation git log documentation git rev list documentation git blame documentation describes showing what revision and author last modified each line of a file git log documentation describes showing commit logs git rev list documentation describes listing commit objects in reverse chronological order by default", "routes": { "html": "https://anchorfact.org/computer-science/code-git-blame-and-commit-history-for-agents/", "markdown": "https://anchorfact.org/computer-science/code-git-blame-and-commit-history-for-agents/index.md", "jsonld": "https://anchorfact.org/computer-science/code-git-blame-and-commit-history-for-agents/index.json", "text": "https://anchorfact.org/computer-science/code-git-blame-and-commit-history-for-agents/index.txt", "turtle": "https://anchorfact.org/computer-science/code-git-blame-and-commit-history-for-agents/index.ttl" } }, { "canonical_slug": "computer-science/code-git-submodules-and-sparse-checkout-for-agents", "title": "Code Git Submodules and Sparse Checkout for Agents", "url": "https://anchorfact.org/computer-science/code-git-submodules-and-sparse-checkout-for-agents/", "description": "Git submodules and sparse checkout evidence helps repository agents avoid missing code that is present only through pinned external repositories or hidden outside the current working tree.", "confidence_level": "medium", "confidence_score": 0.685, "source_coverage": { "verified": 2, "total": 2, "ratio": 1 }, "source_count": 2, "source_tiers": [ "B" ], "source_titles": [ "Git Book Submodules", "Git Sparse Checkout" ], "claim_count": 3, "claim_ids": [ "https://anchorfact.org/fact/fact-cs-code-git-submodules-and-sparse-checkout-for-agents-1", "https://anchorfact.org/fact/fact-cs-code-git-submodules-and-sparse-checkout-for-agents-2", "https://anchorfact.org/fact/fact-cs-code-git-submodules-and-sparse-checkout-for-agents-3" 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"html": "https://anchorfact.org/computer-science/code-git-submodules-and-sparse-checkout-for-agents/", "markdown": "https://anchorfact.org/computer-science/code-git-submodules-and-sparse-checkout-for-agents/index.md", "jsonld": "https://anchorfact.org/computer-science/code-git-submodules-and-sparse-checkout-for-agents/index.json", "text": "https://anchorfact.org/computer-science/code-git-submodules-and-sparse-checkout-for-agents/index.txt", "turtle": "https://anchorfact.org/computer-science/code-git-submodules-and-sparse-checkout-for-agents/index.ttl" } }, { "canonical_slug": "computer-science/code-git-worktrees-and-detached-head-state-for-agents", "title": "Code Git Worktrees and Detached HEAD State for Agents", "url": "https://anchorfact.org/computer-science/code-git-worktrees-and-detached-head-state-for-agents/", "description": "Git worktree and detached-HEAD evidence helps code agents avoid editing the wrong checkout or losing commits off a branch.", "confidence_level": "medium", 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code agents avoid editing the wrong checkout or losing commits off a branch git worktree documentation git checkout documentation git worktree documentation describes git worktree as managing multiple working trees attached to the same repository git worktree documentation says a repository has one main working tree and zero or more linked working trees git checkout documentation describes detached head state as head referring directly to a commit rather than to a branch", "routes": { "html": "https://anchorfact.org/computer-science/code-git-worktrees-and-detached-head-state-for-agents/", "markdown": "https://anchorfact.org/computer-science/code-git-worktrees-and-detached-head-state-for-agents/index.md", "jsonld": "https://anchorfact.org/computer-science/code-git-worktrees-and-detached-head-state-for-agents/index.json", "text": "https://anchorfact.org/computer-science/code-git-worktrees-and-detached-head-state-for-agents/index.txt", "turtle": 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code navigation uses the language agnostic scip code intelligence protocol and falls back to search based navigation when precise data is absent", "routes": { "html": "https://anchorfact.org/computer-science/code-graphs-and-code-intelligence/", "markdown": "https://anchorfact.org/computer-science/code-graphs-and-code-intelligence/index.md", "jsonld": "https://anchorfact.org/computer-science/code-graphs-and-code-intelligence/index.json", "text": "https://anchorfact.org/computer-science/code-graphs-and-code-intelligence/index.txt", "turtle": "https://anchorfact.org/computer-science/code-graphs-and-code-intelligence/index.ttl" } }, { "canonical_slug": "computer-science/code-index-formats-lsif-and-scip", "title": "Code Index Formats: LSIF and SCIP", "url": "https://anchorfact.org/computer-science/code-index-formats-lsif-and-scip/", "description": "LSIF and SCIP let agents consume precomputed code intelligence instead of re-parsing every repository from scratch.", "confidence_level": "medium", "confidence_score": 0.865, "source_coverage": { "verified": 3, "total": 3, "ratio": 1 }, "source_count": 3, "source_tiers": [ "B", "S" ], "source_titles": [ "LSIF 0.6 Specification", "Sourcegraph Writing an Indexer", "SCIP Repository" ], "claim_count": 3, "claim_ids": [ "https://anchorfact.org/fact/fact-cs-code-index-formats-lsif-and-scip-1", "https://anchorfact.org/fact/fact-cs-code-index-formats-lsif-and-scip-2", "https://anchorfact.org/fact/fact-cs-code-index-formats-lsif-and-scip-3" ], "keywords": [ "scip", "code", "lsif", "describes", "index", "repository", "formats", "intelligence", "sourcegraph", "specification", "agents", "computer", "consume", "documentation", "emit", "every", "form", "format", "indexer", "instead", "knowledge", "language", "let", "machine" ], "search_text": "computer science code index formats lsif and scip code index formats lsif and scip lsif and scip let agents consume precomputed code intelligence instead of re parsing every repository from scratch lsif 0 6 specification sourcegraph writing an indexer scip repository the lsif specification describes a format for language servers or other programming tools to emit knowledge about a code workspace sourcegraph documentation says the scip protobuf schema describes the structure of a scip index in machine readable form the scip repository describes scip as a code intelligence protocol", "routes": { "html": "https://anchorfact.org/computer-science/code-index-formats-lsif-and-scip/", "markdown": "https://anchorfact.org/computer-science/code-index-formats-lsif-and-scip/index.md", "jsonld": "https://anchorfact.org/computer-science/code-index-formats-lsif-and-scip/index.json", "text": "https://anchorfact.org/computer-science/code-index-formats-lsif-and-scip/index.txt", "turtle": "https://anchorfact.org/computer-science/code-index-formats-lsif-and-scip/index.ttl" } }, { "canonical_slug": "computer-science/code-junit-xml-test-reports-and-ci-failure-context", "title": "Code JUnit XML 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stalled or at risk of retaining too much source log history debezium monitoring postgresql pg replication slots mysql show replica status debezium documentation describes monitoring metrics for connectors and tasks through jmx mbeans postgresql documentation describes pg replication slots as a view that lists replication slots and their state mysql documentation describes show replica status as a statement that provides status information about replica threads", "routes": { "html": "https://anchorfact.org/computer-science/data-cdc-lag-and-replication-slots/", "markdown": "https://anchorfact.org/computer-science/data-cdc-lag-and-replication-slots/index.md", "jsonld": "https://anchorfact.org/computer-science/data-cdc-lag-and-replication-slots/index.json", "text": "https://anchorfact.org/computer-science/data-cdc-lag-and-replication-slots/index.txt", "turtle": "https://anchorfact.org/computer-science/data-cdc-lag-and-replication-slots/index.ttl" } }, { "canonical_slug": 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facet for describing column level lineage openmetadata documentation describes column level lineage as showing how columns are transformed across assets databricks unity catalog documentation describes data lineage across tables columns notebooks workflows and dashboards", "routes": { "html": "https://anchorfact.org/computer-science/data-column-level-lineage-and-impact-analysis/", "markdown": "https://anchorfact.org/computer-science/data-column-level-lineage-and-impact-analysis/index.md", "jsonld": "https://anchorfact.org/computer-science/data-column-level-lineage-and-impact-analysis/index.json", "text": "https://anchorfact.org/computer-science/data-column-level-lineage-and-impact-analysis/index.txt", "turtle": "https://anchorfact.org/computer-science/data-column-level-lineage-and-impact-analysis/index.ttl" } }, { "canonical_slug": "computer-science/data-column-masking-and-dynamic-data-masking", "title": "Data Column Masking and Dynamic Data Masking", "url": "https://anchorfact.org/computer-science/data-column-masking-and-dynamic-data-masking/", "description": "Column masking and dynamic data masking let data systems expose useful query results while hiding sensitive values from unauthorized identities.", "confidence_level": "medium", "confidence_score": 0.725, "source_coverage": { "verified": 3, "total": 3, "ratio": 1 }, "source_count": 3, "source_tiers": [ "B" ], "source_titles": [ "Snowflake Column-Level Security", "BigQuery Column-Level Security", "SQL Server Dynamic Data Masking" ], "claim_count": 3, "claim_ids": [ "https://anchorfact.org/fact/fact-cs-data-column-masking-and-dynamic-data-masking-1", "https://anchorfact.org/fact/fact-cs-data-column-masking-and-dynamic-data-masking-2", "https://anchorfact.org/fact/fact-cs-data-column-masking-and-dynamic-data-masking-3" ], "keywords": [ "data", "masking", "column", "dynamic", "level", "describes", "documentation", "sensitive", "access", "bigquery", "columns", "security", "server", 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recommends querying only the columns needed instead of using select apache parquet documentation describes file metadata that includes row groups and column chunks apache iceberg documentation says table metadata can be used to plan efficient scans and avoid reading unnecessary files", "routes": { "html": "https://anchorfact.org/computer-science/data-column-pruning-and-file-statistics/", "markdown": "https://anchorfact.org/computer-science/data-column-pruning-and-file-statistics/index.md", "jsonld": "https://anchorfact.org/computer-science/data-column-pruning-and-file-statistics/index.json", "text": "https://anchorfact.org/computer-science/data-column-pruning-and-file-statistics/index.txt", "turtle": "https://anchorfact.org/computer-science/data-column-pruning-and-file-statistics/index.ttl" } }, { "canonical_slug": "computer-science/data-contracts-and-schema-evolution", "title": "Data Contracts and Schema Evolution", "url": 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"compatible", "computer", "constraints", "consumers" ], "search_text": "computer science data contracts and schema evolution data contracts and schema evolution data contracts and schema evolution policies tell agents whether an upstream change is compatible with downstream consumers confluent schema evolution aws glue schema registry dbt model contracts confluent schema registry documentation describes compatibility checking by versioning each schema and comparing new schemas with previous versions aws glue schema registry documentation says compatibility modes form the contract between applications producing and consuming data dbt documentation describes model contracts as allowing users to define columns data types and constraints that dbt enforces", "routes": { "html": "https://anchorfact.org/computer-science/data-contracts-and-schema-evolution/", "markdown": "https://anchorfact.org/computer-science/data-contracts-and-schema-evolution/index.md", "jsonld": 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the contract soda data contracts documentation says contracts enforce data quality standards in a pipeline to prevent negative downstream impact openmetadata documentation says data contracts define schema quality expectations sla guarantees and governance rules for data assets", "routes": { "html": "https://anchorfact.org/computer-science/data-contracts-for-pipelines/", "markdown": "https://anchorfact.org/computer-science/data-contracts-for-pipelines/index.md", "jsonld": "https://anchorfact.org/computer-science/data-contracts-for-pipelines/index.json", "text": "https://anchorfact.org/computer-science/data-contracts-for-pipelines/index.txt", "turtle": "https://anchorfact.org/computer-science/data-contracts-for-pipelines/index.ttl" } }, { "canonical_slug": "computer-science/data-databricks-unity-catalog-lineage-and-permissions", "title": "Data Databricks Unity Catalog Lineage and Permissions", "url": 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"explain", "footer", "help" ], "search_text": "computer science data orc stripes and column statistics data orc stripes and column statistics orc stripes and column statistics help data agents explain why analytical queries can skip or scan large parts of a file orc specification v1 apache orc indexes apache orc specification describes orc file content as divided into stripes apache orc specification says each stripe contains index data row data and a stripe footer apache orc indexes documentation describes file level stripe level and row level indexes as statistics about column values", "routes": { "html": "https://anchorfact.org/computer-science/data-orc-stripes-and-column-statistics/", "markdown": "https://anchorfact.org/computer-science/data-orc-stripes-and-column-statistics/index.md", "jsonld": "https://anchorfact.org/computer-science/data-orc-stripes-and-column-statistics/index.json", "text": 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"computer science data policy tags and sensitive column governance data policy tags and sensitive column governance policy tags turn sensitive column classification into enforceable metadata so agents should inspect both schema tags and access roles before answering data access questions bigquery column level access control bigquery information schema columns bigquery column level security documentation says a table schema must be updated to set a policy tag on a column bigquery documentation says users querying data protected by column level access control need the data catalog fine grained reader role bigquery information schema columns includes a policy tags field listing policy tags attached to a column", "routes": { "html": "https://anchorfact.org/computer-science/data-policy-tags-and-sensitive-column-governance/", "markdown": "https://anchorfact.org/computer-science/data-policy-tags-and-sensitive-column-governance/index.md", "jsonld": 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validation rules data quality expectations and validation rules data quality expectations and validation rules give agents executable evidence about whether a dataset is fit for use great expectations run validations dbt data tests sodacl overview great expectations documentation describes running validations by validating expectations against data and exploring the results dbt documentation describes data tests as assertions about models and other resources in a dbt project sodacl documentation describes soda checks language as a yaml based language for data quality checks", "routes": { "html": "https://anchorfact.org/computer-science/data-quality-expectations-and-validation-rules/", "markdown": "https://anchorfact.org/computer-science/data-quality-expectations-and-validation-rules/index.md", "jsonld": "https://anchorfact.org/computer-science/data-quality-expectations-and-validation-rules/index.json", "text": 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generating statistics inferring schemas and detecting anomalies in data great expectations documentation describes gx as a platform for validating documenting and profiling data quality deequ documentation describes a library built on apache spark for defining unit tests for data and measuring data quality", "routes": { "html": "https://anchorfact.org/computer-science/data-quality-validation-for-ml-pipelines/", "markdown": "https://anchorfact.org/computer-science/data-quality-validation-for-ml-pipelines/index.md", "jsonld": "https://anchorfact.org/computer-science/data-quality-validation-for-ml-pipelines/index.json", "text": "https://anchorfact.org/computer-science/data-quality-validation-for-ml-pipelines/index.txt", "turtle": "https://anchorfact.org/computer-science/data-quality-validation-for-ml-pipelines/index.ttl" } }, { "canonical_slug": "computer-science/data-redshift-system-tables-and-query-monitoring", "title": "Data Redshift System Tables and Query Monitoring", "url": 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partitions when filters use the partitioning column snowflake documentation describes clustering keys as a way to co locate similar rows in the same micro partitions amazon redshift documentation says sort keys determine the order in which rows are stored", "routes": { "html": "https://anchorfact.org/computer-science/data-warehouse-partition-pruning-and-clustering/", "markdown": "https://anchorfact.org/computer-science/data-warehouse-partition-pruning-and-clustering/index.md", "jsonld": "https://anchorfact.org/computer-science/data-warehouse-partition-pruning-and-clustering/index.json", "text": "https://anchorfact.org/computer-science/data-warehouse-partition-pruning-and-clustering/index.txt", "turtle": "https://anchorfact.org/computer-science/data-warehouse-partition-pruning-and-clustering/index.ttl" } }, { "canonical_slug": "computer-science/data-warehouse-query-history-and-job-metadata", "title": "Data Warehouse Query History and Job Metadata", "url": 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expanding ancient state augustus is identified by britannica as the first roman emperor britannica defines the pax romana as a period of comparative tranquillity from augustus to marcus aurelius", "routes": { "html": "https://anchorfact.org/history/ancient-rome/", "markdown": "https://anchorfact.org/history/ancient-rome/index.md", "jsonld": "https://anchorfact.org/history/ancient-rome/index.json", "text": "https://anchorfact.org/history/ancient-rome/index.txt", "turtle": "https://anchorfact.org/history/ancient-rome/index.ttl" } }, { "canonical_slug": "history/aztec-empire", "title": "Aztec Empire", "url": "https://anchorfact.org/history/aztec-empire/", "description": "The Aztec Empire was a central Mexican imperial power with Tenochtitlan as its capital. 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xerox parc 1973 apple macintosh 1984 windows 1985", "routes": { "html": "https://anchorfact.org/history/computer-history/", "markdown": "https://anchorfact.org/history/computer-history/index.md", "jsonld": "https://anchorfact.org/history/computer-history/index.json", "text": "https://anchorfact.org/history/computer-history/index.txt", "turtle": "https://anchorfact.org/history/computer-history/index.ttl" } }, { "canonical_slug": "history/enlightenment-era", "title": "Enlightenment Era", "url": "https://anchorfact.org/history/enlightenment-era/", "description": "The Enlightenment was a broad intellectual movement in seventeenth- and eighteenth-century Europe that emphasized reason, criticism, science, and reform.", "confidence_level": "medium", "confidence_score": 0.725, "source_coverage": { "verified": 3, "total": 3, "ratio": 1 }, "source_count": 3, "source_tiers": [ "B" ], "source_titles": [ "Enlightenment", "The Spirit of Laws", "Enlightenment Stanford Encyclopedia of Philosophy" ], 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This repaired entry uses Britannica for the dynasty and Zheng He's voyages, plus UNESCO for the Forbidden City and imperial-palace context.", "confidence_level": "medium", "confidence_score": 0.725, "source_coverage": { "verified": 3, "total": 3, "ratio": 1 }, "source_count": 3, "source_tiers": [ "B" ], "source_titles": [ "Ming dynasty", "Zheng He", "Imperial Palaces of the Ming and Qing Dynasties in Beijing and Shenyang" ], "claim_count": 3, "claim_ids": [ "https://anchorfact.org/fact/fact-ming-dynasty-001", "https://anchorfact.org/fact/fact-ming-dynasty-002", "https://anchorfact.org/fact/fact-ming-dynasty-003" ], "keywords": [ "ming", "dynasty", "zheng", "1368", "1644", "beijing", "china", "city", "forbidden", "imperial", "ruled", "unesco", "beginning", "britannica", "centuries", "century", "commanded", "context", "describes", "dynasties", "early", "entry", "expeditions", "fifteenth" ], "search_text": "history ming dynasty ming dynasty the ming dynasty ruled china from 1368 to 1644 this repaired entry uses britannica for the dynasty and zheng he s voyages plus unesco for the forbidden city and imperial palace context ming dynasty zheng he imperial palaces of the ming and qing dynasties in beijing and shenyang the ming dynasty ruled china from 1368 to 1644 zheng he commanded large ming maritime expeditions in the early fifteenth century unesco describes the forbidden city in beijing as a seat of supreme power for more than five centuries beginning in the ming period", "routes": { "html": "https://anchorfact.org/history/ming-dynasty/", "markdown": "https://anchorfact.org/history/ming-dynasty/index.md", "jsonld": "https://anchorfact.org/history/ming-dynasty/index.json", "text": "https://anchorfact.org/history/ming-dynasty/index.txt", "turtle": "https://anchorfact.org/history/ming-dynasty/index.ttl" } }, { "canonical_slug": "history/mongol-empire", "title": "Mongol Empire", "url": "https://anchorfact.org/history/mongol-empire/", "description": "The Mongol Empire expanded from Chinggis Khan conquests into the largest contiguous land empire in history. 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This repaired entry narrows the public facts to Britannica overview pages and Roberts's biography.", "confidence_level": "medium", "confidence_score": 0.725, "source_coverage": { "verified": 3, "total": 3, "ratio": 1 }, "source_count": 3, "source_tiers": [ "B" ], "source_titles": [ "Napoleonic Wars", "The Napoleonic era", "Napoleon: A Life" ], "claim_count": 3, "claim_ids": [ "https://anchorfact.org/fact/fact-napoleon-1", "https://anchorfact.org/fact/fact-napoleon-2", "https://anchorfact.org/fact/fact-napoleon-3" ], "keywords": [ "napoleonic", "era", "european", "biography", "britannica", "french", "history", "imperial", "napoleon", "revolutionary", "roberts", "wars", "andrew", "coalition", "coalitions", "conflict", "conflicts", "defeat", "empire", "entry", "exile", "facts", "follows", "france" ], "search_text": "history napoleonic era napoleonic era the napoleonic era reshaped european politics through revolutionary war french imperial rule legal reforms and coalition conflict this repaired entry narrows the public facts to britannica overview pages and roberts s biography napoleonic wars the napoleonic era napoleon a life the napoleonic wars were a series of conflicts involving napoleonic france and shifting coalitions of european powers britannica places the napoleonic era within a wider european history of revolutionary and imperial transformation andrew roberts s biography follows napoleon from his rise through the french revolution to empire defeat and exile", "routes": { "html": "https://anchorfact.org/history/napoleonic-era/", "markdown": "https://anchorfact.org/history/napoleonic-era/index.md", "jsonld": "https://anchorfact.org/history/napoleonic-era/index.json", "text": "https://anchorfact.org/history/napoleonic-era/index.txt", "turtle": "https://anchorfact.org/history/napoleonic-era/index.ttl" } }, { "canonical_slug": "history/ottoman-empire", "title": "Ottoman Empire", "url": "https://anchorfact.org/history/ottoman-empire/", "description": "The Ottoman Empire grew from an Anatolian principality into a multi-century imperial power centered after Constantinople conquest. 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this entry is low confidence because it is anchored to one broad history of science source the scientists john gribbin the scientists by john gribbin is a broad historical source for introducing the development of modern science from renaissance era natural philosophy onward a cautious renaissance science primer can discuss observation instruments mathematics print culture and challenges to inherited authority as broad themes specific claims about vesalius galileo or copernicus need narrower source mapping than this one book primer provides", "routes": { "html": "https://anchorfact.org/history/renaissance-science/", "markdown": "https://anchorfact.org/history/renaissance-science/index.md", "jsonld": "https://anchorfact.org/history/renaissance-science/index.json", "text": "https://anchorfact.org/history/renaissance-science/index.txt", "turtle": "https://anchorfact.org/history/renaissance-science/index.ttl" } }, { "canonical_slug": "history/rise-of-islam", "title": "Rise of Islam", 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muhammad s preaching in arabia the hijrah to medina and the formation of early caliphal rule britannica islam britannica hijrah britannica caliphate britannica identifies islam as a major world religion that began in arabia and is associated with the prophet muhammad the hijrah was muhammad s migration to medina and became the starting point for the islamic era britannica describes the caliphate as the political religious state of the muslim community after muhammad", "routes": { "html": "https://anchorfact.org/history/rise-of-islam/", "markdown": "https://anchorfact.org/history/rise-of-islam/index.md", "jsonld": "https://anchorfact.org/history/rise-of-islam/index.json", "text": "https://anchorfact.org/history/rise-of-islam/index.txt", "turtle": "https://anchorfact.org/history/rise-of-islam/index.ttl" } }, { "canonical_slug": "history/roman-empire", "title": "Roman Empire", "url": "https://anchorfact.org/history/roman-empire/", "description": "The Roman Empire began under Augustus in 27 BCE and became the central imperial phase of ancient Roman history.", "confidence_level": "medium", "confidence_score": 0.725, "source_coverage": { "verified": 3, "total": 3, "ratio": 1 }, "source_count": 3, "source_tiers": [ "B" ], "source_titles": [ "Britannica: Roman Empire", "Britannica: Augustus", "Britannica: Pax Romana" ], "claim_count": 3, "claim_ids": [ "https://anchorfact.org/fact/fact-roman-empire-1", "https://anchorfact.org/fact/fact-roman-empire-2", "https://anchorfact.org/fact/fact-roman-empire-3" ], "keywords": [ "roman", "britannica", "empire", "augustus", "bce", "history", "pax", "romana", "5th", "ancient", "aurelius", "became", "began", "central", "century", "comparative", "dates", "describes", "emperor", "fall", "first", "identifies", "imperial", "marcus" ], "search_text": "history roman empire roman empire the roman empire began under augustus in 27 bce and became the central imperial phase of ancient roman history britannica roman empire britannica augustus britannica pax romana britannica dates the roman empire from 27 bce after the fall of the roman republic through the western empire in the 5th century ce britannica identifies augustus as rome first emperor ruling from 27 bce to 14 ce britannica describes the pax romana as a period of comparative tranquility from augustus to marcus aurelius", "routes": { "html": "https://anchorfact.org/history/roman-empire/", "markdown": "https://anchorfact.org/history/roman-empire/index.md", "jsonld": "https://anchorfact.org/history/roman-empire/index.json", "text": "https://anchorfact.org/history/roman-empire/index.txt", "turtle": "https://anchorfact.org/history/roman-empire/index.ttl" } }, { "canonical_slug": "history/samurai-history", "title": "Samurai History", "url": "https://anchorfact.org/history/samurai-history/", "description": "Samurai history covers warrior status, political service, martial culture, and later ideals such as bushido. This repair removes broad anecdotal claims and keeps three source-mapped facts.", "confidence_level": "medium", "confidence_score": 0.725, "source_coverage": { "verified": 3, "total": 3, "ratio": 1 }, "source_count": 3, "source_tiers": [ "B" ], "source_titles": [ "Samurai", "Bushido", "Miyamoto Musashi" ], "claim_count": 3, "claim_ids": [ "https://anchorfact.org/fact/fact-samurai-1", "https://anchorfact.org/fact/fact-samurai-2", "https://anchorfact.org/fact/fact-samurai-3" ], "keywords": [ "samurai", "history", "bushido", "warrior", "associated", "class", "miyamoto", "musashi", "anecdotal", "author", "became", "book", "broad", "claims", "code", "covers", "culture", "during", "early", "ethos", "facts", "five", "ideals", "important" ], "search_text": "history samurai history samurai history samurai history covers warrior status political service martial culture and later ideals such as bushido this repair removes broad anecdotal claims and keeps three source mapped facts samurai bushido miyamoto musashi samurai were members of japan s warrior class that became politically important during the medieval and early modern periods bushido refers to the code or ethos associated with the samurai warrior class miyamoto musashi was a japanese swordsman and author associated with the book of five rings", "routes": { "html": "https://anchorfact.org/history/samurai-history/", "markdown": "https://anchorfact.org/history/samurai-history/index.md", "jsonld": "https://anchorfact.org/history/samurai-history/index.json", "text": "https://anchorfact.org/history/samurai-history/index.txt", "turtle": "https://anchorfact.org/history/samurai-history/index.ttl" } }, { "canonical_slug": "history/scientific-revolution", "title": "The Scientific Revolution: From Copernicus to Newton", "url": "https://anchorfact.org/history/scientific-revolution/", "description": "The Scientific Revolution (1543-1687) replaced medieval Aristotelian cosmology with empirical observation and mathematical law. Copernicus, Galileo, Kepler, and Newton established the foundations of modern science.", "confidence_level": "medium", "confidence_score": 0.725, "source_coverage": { "verified": 3, "total": 3, "ratio": 1 }, "source_count": 3, "source_tiers": [ "B" ], "source_titles": [ "Scientific Revolution", "The Copernican revolution", "Principia" ], "claim_count": 3, "claim_ids": [ "https://anchorfact.org/fact/af-history-scientific-revolution-1", "https://anchorfact.org/fact/af-history-scientific-revolution-2", "https://anchorfact.org/fact/af-history-scientific-revolution-3" ], "keywords": [ "revolution", "scientific", "britannica", "copernicus", "1543", "1687", "mathematical", "newton", "principia", "aristotelian", "astronomy", "coelestium", "copernican", "cosmology", "describes", "emerged", "empirical", "established", "explanation", "foundations", "galileo", "heliocentric", "history", "identifies" ], "search_text": "history scientific revolution the scientific revolution from copernicus to newton the scientific revolution 1543 1687 replaced medieval aristotelian cosmology with empirical observation and mathematical law copernicus galileo kepler and newton established the foundations of modern science scientific revolution the copernican revolution principia britannica describes the scientific revolution as a transformation in views of nature explanation and method that emerged from the renaissance and reformation britannica notes that copernicus published de revolutionibus orbium coelestium in 1543 making heliocentric astronomy a reference point for later research britannica identifies newtons principia as the 1687 mathematical principles of natural philosophy", "routes": { "html": "https://anchorfact.org/history/scientific-revolution/", "markdown": "https://anchorfact.org/history/scientific-revolution/index.md", "jsonld": "https://anchorfact.org/history/scientific-revolution/index.json", "text": "https://anchorfact.org/history/scientific-revolution/index.txt", "turtle": "https://anchorfact.org/history/scientific-revolution/index.ttl" } }, { "canonical_slug": "history/silk-road", "title": "Silk Road", "url": "https://anchorfact.org/history/silk-road/", "description": "The Silk Road is better understood as a set of connected exchange networks than as one literal road. This low-confidence primer uses one broad world-history source to introduce Eurasian movement of goods, ideas, religions, technologies, and political influence.", "confidence_level": "low", "confidence_score": 0.555, "source_coverage": { "verified": 1, "total": 1, "ratio": 1 }, "source_count": 1, "source_tiers": [ "B" ], "source_titles": [ "The Silk Roads: A New History of the World (Peter Frankopan)" ], "claim_count": 3, "claim_ids": [ "https://anchorfact.org/fact/fact-history-001", "https://anchorfact.org/fact/fact-history-002", "https://anchorfact.org/fact/fact-history-003" ], "keywords": [ "road", "silk", "history", "one", "world", "eurasian", "exchange", "frankopan", "goods", "ideas", "influence", "literal", "movement", "networks", "peter", "political", "primer", "religions", "roads", "source", "technologies", "than", "across", "better" ], "search_text": "history silk road silk road the silk road is better understood as a set of connected exchange networks than as one literal road this low confidence primer uses one broad world history source to introduce eurasian movement of goods ideas religions technologies and political influence the silk roads a new history of the world peter frankopan peter frankopan s the silk roads frames eurasian connections as central to world history a cautious silk road primer can describe the subject as networks of exchange rather than one literal road the source supports an introductory focus on long distance movement of goods ideas religions technologies and political influence across eurasia", "routes": { "html": "https://anchorfact.org/history/silk-road/", "markdown": "https://anchorfact.org/history/silk-road/index.md", "jsonld": "https://anchorfact.org/history/silk-road/index.json", "text": "https://anchorfact.org/history/silk-road/index.txt", "turtle": "https://anchorfact.org/history/silk-road/index.ttl" } }, { "canonical_slug": "history/space-race", "title": "Space Race", "url": "https://anchorfact.org/history/space-race/", "description": "The Space Race is commonly tracked through milestones such as Sputnik, Yuri Gagarin's orbital flight, and Apollo 11.", "confidence_level": "medium", "confidence_score": 0.8, "source_coverage": { "verified": 3, "total": 3, "ratio": 1 }, "source_count": 3, "source_tiers": [ "A" ], "source_titles": [ "NASA: Sputnik and the Dawn of the Space Age", "NASA: Yuri Gagarin Becomes the First Person in Space", "NASA: Apollo 11 Mission Overview" ], "claim_count": 3, "claim_ids": [ "https://anchorfact.org/fact/fact-space-race-1", "https://anchorfact.org/fact/fact-space-race-2", "https://anchorfact.org/fact/fact-space-race-3" ], "keywords": [ "space", "nasa", "apollo", "first", "gagarin", "race", "sputnik", "yuri", "age", "describes", "mission", "person", "1957", "1961", "1969", "becomes", "commonly", "dawn", "event", "flight", "history", "humans", "identifies", "landed" ], "search_text": "history space race space race the space race is commonly tracked through milestones such as sputnik yuri gagarin s orbital flight and apollo 11 nasa sputnik and the dawn of the space age nasa yuri gagarin becomes the first person in space nasa apollo 11 mission overview nasa describes sputnik as the event that opened the space age in 1957 nasa identifies yuri gagarin as the first person in space in 1961 nasa describes apollo 11 as the mission that landed the first humans on the moon in 1969", "routes": { "html": "https://anchorfact.org/history/space-race/", "markdown": "https://anchorfact.org/history/space-race/index.md", "jsonld": "https://anchorfact.org/history/space-race/index.json", "text": "https://anchorfact.org/history/space-race/index.txt", "turtle": "https://anchorfact.org/history/space-race/index.ttl" } }, { "canonical_slug": "history/tang-dynasty", "title": "Tang Dynasty", "url": "https://anchorfact.org/history/tang-dynasty/", "description": "The Tang dynasty ruled China from 618 to 907 and is often treated as a high point of imperial Chinese culture. This repair keeps the public facts to three sourced anchors: the dynasty dates, An Lushan's rebellion, and the Met Museum's overview of Tang cosmopolitan culture.", "confidence_level": "medium", "confidence_score": 0.725, "source_coverage": { "verified": 3, "total": 3, "ratio": 1 }, "source_count": 3, "source_tiers": [ "B" ], "source_titles": [ "Tang dynasty", "An Lushan", "Tang Dynasty (618-906)" ], "claim_count": 3, "claim_ids": [ "https://anchorfact.org/fact/fact-tang-dynasty-001", "https://anchorfact.org/fact/fact-tang-dynasty-002", "https://anchorfact.org/fact/fact-tang-dynasty-003" ], "keywords": [ "tang", "dynasty", "618", "lushan", "907", "china", "cosmopolitan", "culture", "met", "museum", "rebellion", "ruled", "755", "906", "anchors", "began", "chinese", "cultural", "dates", "describes", "era", "exchange", "facts", "flourishing" ], "search_text": "history tang dynasty tang dynasty the tang dynasty ruled china from 618 to 907 and is often treated as a high point of imperial chinese culture this repair keeps the public facts to three sourced anchors the dynasty dates an lushan s rebellion and the met museum s overview of tang cosmopolitan culture tang dynasty an lushan tang dynasty 618 906 the tang dynasty ruled china from 618 to 907 an lushan was a tang general whose rebellion began in 755 and seriously weakened the dynasty the met museum describes the tang period as a cosmopolitan era with flourishing trade and cultural exchange", "routes": { "html": "https://anchorfact.org/history/tang-dynasty/", "markdown": "https://anchorfact.org/history/tang-dynasty/index.md", "jsonld": "https://anchorfact.org/history/tang-dynasty/index.json", "text": "https://anchorfact.org/history/tang-dynasty/index.txt", "turtle": "https://anchorfact.org/history/tang-dynasty/index.ttl" } }, { "canonical_slug": "history/viking-age", "title": "Viking Age", "url": "https://anchorfact.org/history/viking-age/", "description": "The Viking Age is usually introduced through Scandinavian seafaring, raiding, trading, exploration, settlement, and cultural change. This entry is intentionally low confidence because it is source-mapped to one broad book source.", "confidence_level": "low", "confidence_score": 0.555, "source_coverage": { "verified": 1, "total": 1, "ratio": 1 }, "source_count": 1, "source_tiers": [ "B" ], "source_titles": [ "The Age of the Vikings (Anders Winroth)" ], "claim_count": 3, "claim_ids": [ "https://anchorfact.org/fact/fact-history-001", "https://anchorfact.org/fact/fact-history-002", "https://anchorfact.org/fact/fact-history-003" ], "keywords": [ "age", "viking", "source", "change", "cultural", "mapped", "raiding", "scandinavian", "seafaring", "settlement", "vikings", "activity", "alone", "anders", "arts", "book", "broad", "colonization", "commerce", "confidence", "describe", "discovery", "entry", "exploration" ], "search_text": "history viking age viking age the viking age is usually introduced through scandinavian seafaring raiding trading exploration settlement and cultural change this entry is intentionally low confidence because it is source mapped to one broad book source the age of the vikings anders winroth the age of the vikings presents the viking period through raids as well as commerce politics discovery colonization arts literature and religious thought a source mapped viking age primer should therefore describe norse activity as more than raiding alone the source supports an introductory focus on scandinavian seafaring travel settlement trade political change and cultural production", "routes": { "html": "https://anchorfact.org/history/viking-age/", "markdown": "https://anchorfact.org/history/viking-age/index.md", "jsonld": "https://anchorfact.org/history/viking-age/index.json", "text": "https://anchorfact.org/history/viking-age/index.txt", "turtle": "https://anchorfact.org/history/viking-age/index.ttl" } }, { "canonical_slug": "history/vikings-exploration-and-culture", "title": "Vikings: Exploration and Culture", "url": "https://anchorfact.org/history/vikings-exploration-and-culture/", "description": "The Vikings entry is narrowed to directly supported claims about Scandinavian seafaring activity, Norse settlement evidence in Newfoundland, and the role of ships in Viking mobility.", "confidence_level": "medium", "confidence_score": 0.725, "source_coverage": { "verified": 3, "total": 3, "ratio": 1 }, "source_count": 3, "source_tiers": [ "B" ], "source_titles": [ "Viking | Britannica", "L'Anse aux Meadows National Historic Site | UNESCO World Heritage Centre", "The Viking Age: The Ships | National Museum of Denmark" ], "claim_count": 3, "claim_ids": [ "https://anchorfact.org/fact/fact-history-01", "https://anchorfact.org/fact/fact-history-02", "https://anchorfact.org/fact/fact-history-03" ], "keywords": [ "viking", "vikings", "describes", "national", "ships", "11th", "anse", "aux", "britannica", "century", "culture", "denmark", "evidence", "exploration", "meadows", "museum", "newfoundland", "norse", "scandinavian", "seafaring", "settlement", "unesco", "9th", "across" ], "search_text": "history vikings exploration and culture vikings exploration and culture the vikings entry is narrowed to directly supported claims about scandinavian seafaring activity norse settlement evidence in newfoundland and the role of ships in viking mobility viking britannica l anse aux meadows national historic site unesco world heritage centre the viking age the ships national museum of denmark britannica describes vikings as scandinavian seafaring raiders traders explorers and colonizers active mainly from the 9th to the 11th century unesco describes l anse aux meadows as an 11th century norse settlement at the tip of newfoundland that provides evidence of early european presence in north america the national museum of denmark describes viking ships as central to viking travel trade and warfare across seas and rivers", "routes": { "html": "https://anchorfact.org/history/vikings-exploration-and-culture/", "markdown": "https://anchorfact.org/history/vikings-exploration-and-culture/index.md", "jsonld": "https://anchorfact.org/history/vikings-exploration-and-culture/index.json", "text": "https://anchorfact.org/history/vikings-exploration-and-culture/index.txt", "turtle": "https://anchorfact.org/history/vikings-exploration-and-culture/index.ttl" } }, { "canonical_slug": "history/world-war-i", "title": "World War I", "url": "https://anchorfact.org/history/world-war-i/", "description": "World War I was a global conflict rooted in alliance systems, imperial rivalry, militarization, and the 1914 July Crisis. 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This repair binds each claim to institutional history sources.", "confidence_level": "medium", "confidence_score": 0.83, "source_coverage": { "verified": 3, "total": 3, "ratio": 1 }, "source_count": 3, "source_tiers": [ "A", "B" ], "source_titles": [ "World War II", "Pearl Harbor Attack", "Surrender of Germany" ], "claim_count": 3, "claim_ids": [ "https://anchorfact.org/fact/fact-world-war-ii-1", "https://anchorfact.org/fact/fact-world-war-ii-2", "https://anchorfact.org/fact/fact-world-war-ii-3" ], "keywords": [ "war", "world", "germany", "harbor", "pearl", "attack", "history", "surrender", "1939", "1941", "1945", "allied", "axis", "began", "binds", "brought", "claim", "december", "defeat", "each", "europe", "global", "institutional", "invaded" ], "search_text": "history world war ii world war ii world war ii was a global war shaped by germany invasion pearl harbor and the allied defeat of axis powers this repair binds each claim to institutional history sources world war ii pearl harbor attack surrender of germany world war ii began in europe after germany invaded poland in september 1939 the japanese attack on pearl harbor on december 7 1941 brought the united states into world war ii germany signed an unconditional surrender at reims on may 7 1945", "routes": { "html": "https://anchorfact.org/history/world-war-ii/", "markdown": "https://anchorfact.org/history/world-war-ii/index.md", "jsonld": "https://anchorfact.org/history/world-war-ii/index.json", "text": "https://anchorfact.org/history/world-war-ii/index.txt", "turtle": "https://anchorfact.org/history/world-war-ii/index.ttl" } }, { "canonical_slug": "history/world-war-ii-overview", "title": "World War II: Global Conflict and Its Aftermath", "url": "https://anchorfact.org/history/world-war-ii-overview/", "description": "World War II was a global conflict from 1939 to 1945 involving the Axis and Allied powers across Europe, Asia, Africa, and the oceans.", "confidence_level": "medium", "confidence_score": 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as a 1939 1945 conflict involving virtually every part of the world imperial war museums describes d day on 6 june 1944 as the largest amphibious invasion in the history of warfare landing more than 150 000 allied troops in normandy britannica places the atomic bombings of hiroshima and nagasaki on 6 august and 9 august 1945 within the final phase of the pacific war", "routes": { "html": "https://anchorfact.org/history/world-war-ii-overview/", "markdown": "https://anchorfact.org/history/world-war-ii-overview/index.md", "jsonld": "https://anchorfact.org/history/world-war-ii-overview/index.json", "text": "https://anchorfact.org/history/world-war-ii-overview/index.txt", "turtle": "https://anchorfact.org/history/world-war-ii-overview/index.ttl" } }, { "canonical_slug": "science/astronomy-and-cosmology", "title": "Astronomy and Cosmology: From Solar System to the Universe", "url": "https://anchorfact.org/science/astronomy-and-cosmology/", "description": "Astronomy and cosmology connect observations of stars, galaxies, black holes, and the expanding universe.", "confidence_level": "medium", "confidence_score": 0.89, "source_coverage": { "verified": 3, "total": 3, "ratio": 1 }, "source_count": 3, "source_tiers": [ "A", "S" ], "source_titles": [ "NASA Science: The Big Bang", "Planck 2018 Results VI Cosmological Parameters", "First M87 Event Horizon Telescope Results I" ], "claim_count": 3, "claim_ids": [ "https://anchorfact.org/fact/fact-astronomy-cosmology-1", "https://anchorfact.org/fact/fact-astronomy-cosmology-2", "https://anchorfact.org/fact/fact-astronomy-cosmology-3" ], "keywords": [ "astronomy", "cosmology", "horizon", "results", "universe", "2018", "bang", "big", "black", "cosmological", "event", "first", "m87", "nasa", "observations", "planck", "science", "telescope", "2019", "ago", "background", "began", "billion", "cdm" ], "search_text": "science astronomy and cosmology astronomy and cosmology from solar system to the universe astronomy and cosmology connect 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