{"id":"W7083434468","doi":"10.1017/jdm.2025.10014","title":"Probability matching and statistical naïveté","year":2025,"lang":"en","type":"article","venue":"Judgment and Decision Making","topic":"Agricultural risk and resilience","field":"Agricultural and Biological Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Matching (statistics); Probability distribution; Cognition; Probability estimation; Statistical power; Probability mass function; Key (lock)","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":[0.0001824615,0.00008624911,0.0001125089,0.000008082997,0.0002814184,0.000111722,0.0000722783,0.00004956301,0.00005777146],"category_scores_gemma":[0.0000544296,0.00002576022,0.00001969053,0.0001314371,0.00005443025,0.00007659618,0.0001533754,0.00007528884,0.000004443497],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001213827,"about_ca_system_score_gemma":0.000002686407,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002421232,"about_ca_topic_score_gemma":0.00007208705,"domain_scores_codex":[0.999283,0.00002221776,0.0001541345,0.0002575795,0.0001399856,0.0001431393],"domain_scores_gemma":[0.9993632,0.0005096044,0.00003007298,0.00002802521,0.00002239579,0.00004670232],"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":[0.00004161772,0.00002424571,0.02953944,0.000009115614,0.000003220021,0.000002931764,0.0000418014,0.000005830751,0.004682626,0.008904052,0.0009238346,0.9558213],"study_design_scores_gemma":[0.00009428159,0.00004961472,0.8856978,0.0001126519,0.00000815503,0.000004920731,0.0002759277,0.0002087284,0.00008130357,0.1086356,0.004723438,0.0001076247],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.996761,0.0005008979,0.001097258,0.0004275777,0.0000718097,0.0001360107,0.000005071402,0.00002754819,0.0009727798],"genre_scores_gemma":[0.995599,0.0001189235,0.00392445,0.0002061519,0.00003255494,0.000004991499,0.000002467617,2.027512e-7,0.0001112682],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9557137,"threshold_uncertainty_score":0.2164471,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02091206097841052,"score_gpt":0.2718046364014454,"score_spread":0.2508925754230348,"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."}}