{"id":"W2136677635","doi":"10.1016/j.tics.2014.06.006","title":"Probabilistic models, learning algorithms, and response variability: sampling in cognitive development","year":2014,"lang":"en","type":"review","venue":"Trends in Cognitive Sciences","topic":"Child and Animal Learning Development","field":"Psychology","cited_by":124,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"National Science Foundation","keywords":"Probabilistic logic; Inference; Sampling (signal processing); Computer science; Cognition; Probability distribution; Computation; Number sense; Statistical inference; Machine learning; Artificial intelligence; Algorithm; Theoretical computer science; Mathematics; Psychology; Cognitive science; Statistics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003141268,0.001044009,0.001674474,0.001717994,0.0002554306,0.002001933,0.002223848,0.002787697,0.002771094],"category_scores_gemma":[0.009001098,0.0005589909,0.0006077135,0.002771385,0.002615457,0.002704122,0.001077867,0.00265637,0.001019942],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00160199,"about_ca_system_score_gemma":0.002331678,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004590585,"about_ca_topic_score_gemma":0.003750279,"domain_scores_codex":[0.9991835,0.0002442124,0.0000788824,0.0001746773,0.0002880428,0.00003078815],"domain_scores_gemma":[0.9932381,0.005396627,0.0003719795,0.0001807268,0.0006895634,0.0001229672],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00004618481,0.00005822788,0.001223637,0.003881963,0.0001018204,0.00006488014,0.0001023047,0.003353131,0.0004033149,0.03483703,0.008519367,0.947408],"study_design_scores_gemma":[0.00005155932,0.0001873817,0.01063475,0.007541323,0.0003104672,0.002153791,0.0003158822,0.01113343,0.002110912,0.2453538,0.7200028,0.0002040267],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0007026681,0.9841576,0.01066776,0.001973924,0.0001840727,0.000009590175,0.00004856068,0.00003994241,0.002215898],"genre_scores_gemma":[0.01012271,0.9815544,0.006127732,0.0004996089,0.0006897958,0.00003560311,0.00006683323,0.000015531,0.0008878273],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.004590585,"threshold_uncertainty_score":0.01661283,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3211989306171728,"score_gpt":0.4727953351431456,"score_spread":0.1515964045259728,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}