{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.03659273,0.0007351227,0.0012665,0.001418423,0.001265071,0.003143342,0.001326203,0.001905181,0.0109803],"category_scores_gemma":[0.2090512,0.0006247474,0.001033754,0.0009053766,0.005663188,0.004757347,0.002160888,0.003197149,0.0007901001],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001588422,"about_ca_system_score_gemma":0.001285928,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002115778,"about_ca_topic_score_gemma":0.001614448,"domain_scores_codex":[0.9661936,0.02195013,0.001597137,0.00542256,0.003893769,0.0009427425],"domain_scores_gemma":[0.7357907,0.2022333,0.02854567,0.02371535,0.007354766,0.002360277],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.003669183,0.002047381,0.3364664,0.001220286,0.001486017,0.000656385,0.010969,0.03572246,0.01068309,0.3831424,0.01009258,0.2038448],"study_design_scores_gemma":[0.0002616072,0.000618753,0.04967328,0.0001672666,0.0001537755,0.0005495467,0.0008235575,0.1548248,0.002721615,0.7866067,0.0034374,0.0001615145],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8116715,0.0005064714,0.1488244,0.00465773,0.0002447231,0.0005975841,0.0002379922,0.0003141332,0.03294554],"genre_scores_gemma":[0.9873223,0.00005615214,0.01090057,0.0005809027,0.00007778724,0.000137532,0.00008554084,0.00002110736,0.0008182542],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03659273,"threshold_uncertainty_score":0.1935232,"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."}}