{"id":"W4319984826","doi":"10.31234/osf.io/s23xu","title":"The Odds Tell Children What People Favor","year":2023,"lang":"en","type":"preprint","venue":"","topic":"Child and Animal Learning Development","field":"Psychology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Chose; Odds; White (mutation); Psychology; Social psychology; Demography; Logistic regression; Sociology; Medicine; Political science; Law","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.001699998,0.0004054531,0.0003256258,0.0007790691,0.0007135454,0.002248719,0.0003292729,0.0009212493,0.005195538],"category_scores_gemma":[0.01076963,0.0005162858,0.0002643863,0.0005259191,0.001273888,0.001746496,0.000705127,0.0008184451,0.0007409084],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001024249,"about_ca_system_score_gemma":0.0005036564,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03622296,"about_ca_topic_score_gemma":0.05567605,"domain_scores_codex":[0.9990729,0.0002195673,0.0000446689,0.0002351114,0.0002931868,0.0001344574],"domain_scores_gemma":[0.9935042,0.002975911,0.002077568,0.0004237089,0.0005972189,0.000421345],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003651911,0.00009595616,0.9328329,0.0001308045,0.00008931091,0.0004436924,0.01909283,0.0003069259,0.004954793,0.005760547,0.001506882,0.03442017],"study_design_scores_gemma":[0.00002376927,0.000170428,0.9658513,0.0001072159,0.0001027637,0.0005504448,0.01196943,0.0006550291,0.003194527,0.00502963,0.01226186,0.00008348213],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9847169,0.0005746665,0.001479656,0.0005147866,0.00001756742,0.00001561105,0.0005755204,0.00003291575,0.0120723],"genre_scores_gemma":[0.9951332,0.0004025868,0.002365936,0.0001794457,0.000009404928,0.00001841847,0.0003462063,0.00001501727,0.00152982],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03622296,"threshold_uncertainty_score":0.07202423,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02952207763642855,"score_gpt":0.3059020766351038,"score_spread":0.2763799989986753,"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."}}