{"id":"W3130812303","doi":"10.1287/orsc.2020.1424","title":"The Politics of Learning from Rare Events","year":2021,"lang":"en","type":"article","venue":"Organization Science","topic":"Evolution and Genetic Dynamics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":23,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Politics; Population; Reliability (semiconductor); Control (management); Sociology; Political science; Computer science; Artificial intelligence; Law","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001006198,0.00003102234,0.00002852884,0.000009443648,0.0002555384,0.00001886864,0.0001521267,0.00002455329,0.00002783967],"category_scores_gemma":[0.000853189,0.00002578441,0.000009581925,0.0003892693,0.0001274264,0.000002461826,0.000108648,0.00002478921,0.000006830804],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000008154732,"about_ca_system_score_gemma":0.0002512808,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003282476,"about_ca_topic_score_gemma":0.000007749129,"domain_scores_codex":[0.9995366,0.00002463107,0.00008273748,0.0001278678,0.0001410774,0.00008707161],"domain_scores_gemma":[0.9992975,0.000008713405,0.00004319548,0.0001616203,0.0004577575,0.00003119431],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[7.067077e-7,0.00001070334,0.0680283,0.000001076078,0.000003577379,1.946402e-7,0.00007312233,0.0008963962,0.9286953,0.001787739,0.0001795974,0.0003232532],"study_design_scores_gemma":[0.0001631875,0.00002732112,0.1081142,0.000005350682,0.000005741091,0.000005884063,0.0006421991,0.001903495,0.8732122,0.0005000414,0.01532988,0.00009051597],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9683212,0.0002367696,0.03040981,0.000290332,0.0001397292,0.00002324278,0.000004314481,0.000005159284,0.000569466],"genre_scores_gemma":[0.9963747,0.0001202143,0.0006111937,0.00007427892,0.00003511369,2.318946e-7,0.00005528852,0.000004490399,0.002724504],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05548319,"threshold_uncertainty_score":0.1965421,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005277577256411274,"score_gpt":0.2350493495621275,"score_spread":0.2297717723057162,"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."}}