RESEARCH BASE

Search 3,721 documents across 34 fields — every claim tier-rated by evidence

3,721 Documents 34 Sections 43,625 Citations 34,852 Keywords Indexed 4 Evidence Tiers

3,633 are the core, quality-scored corpus (34 lettered sections — see How We Work); the remaining 88 are cross-corpus synthesis documents (68 InterDocs, 12 Connections, 8 Theories) also indexed here.

3,721 results for "T Tauri star" — page 112 of 187

ZD_4_14 Verified Information & Computation

ZD_4_14 — Computational Social Science: Agent-Based Modeling, Digital Trace Data, and Social Simulation

Computational social science (CSS) is the interdisciplinary field that applies computational methods — agent-based modeling, social network analysis, natural language processing, machine learning, simulation, and large-s

computational social science agent-based modeling social simulation digital trace data computational text analysis big data
ZD_4_06 Verified Information & Computation

ZD_4_06 — Mathematical Sociology and Network Analysis

Mathematical sociology applies formal mathematical models — graph theory, probability, game theory, dynamical systems, and statistical mechanics — to understand social structures, collective behavior, and institutional d

network analysis social network graph theory small world scale-free network centrality
ZD_4_11 Verified Information & Computation

ZD_4_11 — Social Network Analysis — Granovetter, Small Worlds, Influence

Social network analysis (SNA) — the study of social structures through the use of graph theory and network science, where individuals (or organizations, nations, etc.) are represented as nodes and their relationships (fr

social network analysis network science Granovetter weak ties small world Watts
ZD_4_04 Verified Information & Computation

ZD_4_04 — Mathematical Modeling and Simulation

Mathematical modeling — the art and science of translating real-world phenomena into mathematical language — is how scientists bridge theory and observation. A mathematical model is a simplified mathematical representati

mathematical modeling simulation differential equation model agent-based model compartmental model SIR model
ZD_2_08 Credible Information & Computation

ZD_2_08 — Penrose and Computation: Non-Computability, Consciousness, and Gödel's Theorem

Roger Penrose (b. 1931), Nobel laureate in physics (2020, for demonstrating that black hole formation is a robust prediction of general relativity), has advanced an influential and controversial argument that human mathe

Penrose Gödel non-computability consciousness quantum gravity orchestrated objective reduction
ZD_2_04 Verified Information & Computation

ZD_2_04 — Computer Vision and Image Processing

Computer vision — enabling machines to interpret and understand visual information from the world — has progressed from hand-crafted feature engineering to the deep learning revolution that now approaches or exceeds huma

computer vision image processing convolutional neural network object detection image classification edge detection
ZD_2_16 Credible Information & Computation

ZD_2_16 — Federated Learning & Privacy-Preserving ML

Federated learning (FL) is a machine learning paradigm in which a model is trained across multiple decentralized devices or servers holding local data samples, without exchanging the raw data — the model comes to the dat

federated learning privacy-preserving machine learning differential privacy Google Brendan McMahan data privacy
ZD_2_05 Verified Information & Computation

ZD_2_05 — Robotics and Control Theory

Robotics integrates mechanical engineering, electrical engineering, computer science, and control theory to design, build, and program machines that sense, reason, and act in the physical world. Control theory — the math

robotics control theory feedback control PID controller kinematics dynamics
ZD_2_06 Verified Information & Computation

ZD_2_06 — Ethics of AI and Algorithmic Bias

AI ethics examines the moral implications of designing, deploying, and governing artificial intelligence systems, while algorithmic bias refers to systematic errors in automated decision-making that produce unfair outcom

AI ethics algorithmic bias fairness accountability transparency explainability
ZD_2_15 Verified Information & Computation

ZD_2_15 — Transformer Architecture: Self-Attention and the Foundation of Modern AI

The transformer is a neural network architecture introduced in 2017 that replaced recurrent and convolutional models as the dominant paradigm in artificial intelligence. Its core innovation — the self-attention mechanism

transformer self-attention multi-head attention positional encoding encoder-decoder BERT
ZD_2_03 Verified Information & Computation

ZD_2_03 — Natural Language Processing

Natural language processing (NLP) — the computational analysis, understanding, and generation of human language — spans rule-based, statistical, and neural approaches across tasks including machine translation, text clas

natural language processing NLP computational linguistics parsing sentiment analysis machine translation
ZD_2_02 Verified Information & Computation

ZD_2_02 — Artificial Intelligence Foundations

Artificial intelligence (AI) — the field devoted to creating machines that exhibit intelligent behavior — was formally founded at the Dartmouth Conference (1956) organized by John McCarthy, Marvin Minsky, Nathaniel Roche

artificial intelligence Turing test symbolic AI connectionism neural network expert system
ZD_2_07 Credible Information & Computation

ZD_2_07 — Artificial General Intelligence — Architectures and Challenges

Artificial General Intelligence (AGI) — a hypothetical AI system capable of performing any intellectual task that a human can, with the same flexibility, generality, and ability to learn and transfer knowledge across dom

AGI artificial general intelligence artificial intelligence AI superintelligence alignment
ZD_2_12 Verified Information & Computation

ZD_2_12 — Generative AI: Large Language Models, Diffusion, and the Transformer Revolution

Generative AI refers to artificial intelligence systems capable of creating new content — text, images, audio, video, code, 3D models — that is novel, coherent, and often indistinguishable from human-created work. The fi

generative AI large language model LLM GPT transformer diffusion model
ZD_2_10 Verified Information & Computation

ZD_2_10 — Speech Recognition and Synthesis: From Acoustic Models to Neural Voice Generation

Speech recognition (Automatic Speech Recognition — ASR) and speech synthesis (Text-to-Speech — TTS) are complementary technologies that bridge human spoken language and machine processing. ASR converts spoken audio into

speech recognition ASR text-to-speech TTS voice assistant Whisper
ZD_2_01 Verified Information & Computation

ZD_2_01 — Machine Learning Mathematics

Machine learning — the science of algorithms that improve through experience — rests on a rich mathematical foundation spanning optimization, statistics, linear algebra, probability, and functional analysis. The core mat

machine learning gradient descent backpropagation neural network statistical learning theory VC dimension
ZD_2_14 Verified Information & Computation

ZD_2_14 — Autonomous Systems: Self-Driving Vehicles, Drones, and Safety-Critical AI

Autonomous systems are machines capable of performing complex tasks in unstructured, dynamic environments with limited or no human intervention — perceiving their environment through sensors, making decisions through com

autonomous systems self-driving autonomous vehicles drones robotics perception
ZD_2_17 Credible Information & Computation

ZD_2_17 — AI Alignment & Existential Risk

AI alignment — the challenge of ensuring artificial intelligence systems pursue goals consistent with human values and intentions — has emerged as one of the defining technical and philosophical problems of the 21st cent

AI alignment existential risk superintelligence value alignment instrumental convergence corrigibility
ZD_2_13 Verified Information & Computation

ZD_2_13 — Explainable AI: Interpretability, Trust, and the Black Box Problem

Explainable AI (XAI) is the field concerned with making artificial intelligence systems — particularly complex machine learning models — understandable to humans. As AI systems increasingly make or influence high-stakes

explainable AI XAI interpretability LIME SHAP black box
ZD_2_11 Verified Information & Computation

ZD_2_11 — Reinforcement Learning: Agents, Rewards, and Sequential Decision-Making

Reinforcement learning (RL) is a paradigm of machine learning in which an agent learns to make sequential decisions by interacting with an environment, receiving rewards (or penalties) for its actions, and adjusting its

reinforcement learning MDP Q-learning policy gradient AlphaGo reward