{"id":"W4327675491","doi":"10.3758/s13414-023-02692-7","title":"The relative importance of local contingencies and global biases for statistical learning","year":2023,"lang":"en","type":"article","venue":"Attention Perception & Psychophysics","topic":"Child and Animal Learning Development","field":"Psychology","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Perception; Psychology; Statistical model; Contrast (vision); Task (project management); Cognitive psychology; Statistical learning; Mathematics; Computer science; Statistics; Artificial intelligence","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002902469,0.0001025733,0.0001322008,0.00002227196,0.0003091673,0.00002714462,0.00006238648,0.0000526186,0.00009869683],"category_scores_gemma":[0.00008621976,0.00008249115,0.00007306744,0.0002193775,0.0002298738,0.00006592641,0.0000233871,0.0001195635,0.0001379853],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002696714,"about_ca_system_score_gemma":0.00001350877,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001416644,"about_ca_topic_score_gemma":0.00001226961,"domain_scores_codex":[0.999045,0.00008150439,0.000261341,0.0002619763,0.0001478177,0.0002024256],"domain_scores_gemma":[0.9992613,0.000351101,0.0001456331,0.0001063343,0.00009631427,0.00003934436],"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":[0.000551864,0.0001683673,0.2906449,0.0000543351,0.0002575624,0.000003683949,0.004174661,0.00006215579,0.003675615,0.3309593,0.02336441,0.3460831],"study_design_scores_gemma":[0.0005073248,0.0001784106,0.9786303,0.00003287312,0.00002514627,0.000002436383,0.00678853,0.0004371894,0.00000171358,0.007217865,0.006075651,0.0001025522],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9540665,0.00006498174,0.0427219,0.0006275335,0.0003975943,0.0002156226,0.00004023597,0.00009280547,0.001772861],"genre_scores_gemma":[0.9972247,0.00007293822,0.0005776245,0.00006794754,0.0001008739,0.00004078887,0.0001088911,0.00001204425,0.001794209],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6879854,"threshold_uncertainty_score":0.3363892,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03500131960881549,"score_gpt":0.3484318916291734,"score_spread":0.3134305720203579,"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."}}