{"id":"W2335322209","doi":"10.1037/a0037158","title":"Probability versus representativeness in infancy: Can infants use naïve physics to adjust population base rates in probabilistic inference?","year":2014,"lang":"en","type":"article","venue":"Developmental Psychology","topic":"Child and Animal Learning Development","field":"Psychology","cited_by":26,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Representativeness heuristic; Probabilistic logic; Psychology; Inference; Similarity (geometry); Heuristic; Population; Perception; Cognitive psychology; Probability distribution; Knowledge base; Developmental psychology; Artificial intelligence; Computer science; Statistics; Social psychology; Mathematics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.005916353,0.0004640683,0.0007219844,0.0007342635,0.0003405819,0.001876162,0.001399404,0.001018422,0.001272104],"category_scores_gemma":[0.05020069,0.001188417,0.0007270662,0.0003327787,0.002388983,0.006149226,0.001594317,0.001606375,0.0002921957],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008442151,"about_ca_system_score_gemma":0.0006858733,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002620409,"about_ca_topic_score_gemma":0.001848828,"domain_scores_codex":[0.9976762,0.0006528505,0.0001287916,0.000886107,0.0005035792,0.0001525297],"domain_scores_gemma":[0.9878923,0.006831909,0.001995948,0.002086257,0.00080918,0.0003845759],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0008156445,0.0002617633,0.2647551,0.0007062195,0.0005913292,0.00109924,0.009533491,0.07117061,0.1615082,0.1514554,0.001586084,0.3365169],"study_design_scores_gemma":[0.00009324332,0.0008730439,0.3449033,0.0002110438,0.0002684395,0.001870645,0.001424519,0.2178456,0.05057253,0.3752004,0.006356423,0.0003808848],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6768334,0.0007044878,0.3128682,0.0008078854,0.00005809903,0.00007755263,0.0001194461,0.0006597835,0.007871162],"genre_scores_gemma":[0.945869,0.0003186179,0.0526148,0.0001750018,0.00001926554,0.00007615738,0.00009844582,0.0001604227,0.0006682022],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005916353,"threshold_uncertainty_score":0.03128904,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0999174233712326,"score_gpt":0.3826259459393847,"score_spread":0.2827085225681521,"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."}}