{"id":"W1980572285","doi":"10.3389/fpsyg.2015.00387","title":"Instruction in information structuring improves Bayesian judgment in intelligence analysts","year":2015,"lang":"en","type":"article","venue":"Frontiers in Psychology","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":47,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University; Defence Research and Development Canada","funders":"","keywords":"Structuring; Psychology; Bayesian probability; Intelligence analysis; Cognitive psychology; Cognitive science; Data science; Artificial intelligence; Computer science; Political science","routes":{"ca_aff":true,"ca_fund":false,"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":[0.003613722,0.0006767249,0.0004841633,0.0005494813,0.0004059269,0.001273512,0.0009760988,0.001155198,0.00285917],"category_scores_gemma":[0.0689499,0.0004902806,0.0002006149,0.0002963134,0.0009474471,0.00133564,0.000949374,0.001617944,0.0007348711],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004827133,"about_ca_system_score_gemma":0.001120579,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0015589,"about_ca_topic_score_gemma":0.001381495,"domain_scores_codex":[0.9973132,0.001196096,0.0001866449,0.0005211701,0.0005914054,0.0001914531],"domain_scores_gemma":[0.9467964,0.03913304,0.006920768,0.003574693,0.002017687,0.001557427],"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":[0.008035788,0.0286123,0.07658277,0.0009500981,0.0002369734,0.0005318747,0.0398344,0.006398775,0.248226,0.004148137,0.005622635,0.5808203],"study_design_scores_gemma":[0.005337608,0.0446867,0.5242813,0.0008548117,0.0008616943,0.001245648,0.01279433,0.07922282,0.2521085,0.04810756,0.02978178,0.0007172429],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9930683,0.00007411488,0.004631688,0.0002218603,0.00001622287,0.00007468456,0.00001649537,0.0003131855,0.001583332],"genre_scores_gemma":[0.977979,0.0001346961,0.02060224,0.0001835752,0.00001772799,0.00009015373,0.00008358518,0.00004238873,0.0008667127],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003613722,"threshold_uncertainty_score":0.01911145,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02240247512795242,"score_gpt":0.3161508740113134,"score_spread":0.293748398883361,"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."}}