{"id":"W2148958642","doi":"10.1287/orsc.1080.0389","title":"Learning Through Rare Events: Significant Interruptions at the Baltimore & Ohio Railroad Museum","year":2008,"lang":"en","type":"article","venue":"Organization Science","topic":"Management and Organizational Studies","field":"Business, Management and Accounting","cited_by":389,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Smithsonian Institution; National Science Foundation","keywords":"Event (particle physics); Ambiguity; Rare events; Identity (music); Narrative; History; Point (geometry); Sociology; Computer science; Aesthetics; Art; Literature","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":[0.003234808,0.0002704216,0.000426989,0.00128957,0.009266805,0.004768014,0.001570279,0.001933215,0.003060599],"category_scores_gemma":[0.01488714,0.0003930958,0.0002367474,0.001331345,0.005076695,0.002847408,0.005474083,0.003001688,0.0003516023],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004769936,"about_ca_system_score_gemma":0.002261251,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02555414,"about_ca_topic_score_gemma":0.06294377,"domain_scores_codex":[0.9969578,0.001394953,0.00007802936,0.0002232801,0.0006966211,0.0006492703],"domain_scores_gemma":[0.9911418,0.003766185,0.001507976,0.000641263,0.0005591073,0.002383624],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.0002680469,0.0005845545,0.09374036,0.00016238,0.00005461119,0.00372514,0.8411083,0.0005121685,0.001457345,0.004568657,0.01312643,0.04069211],"study_design_scores_gemma":[0.00002278531,0.0002500698,0.1569899,0.0001505416,0.00003014943,0.0005425902,0.7824048,0.0005025543,0.0006669119,0.002064331,0.05628112,0.00009422754],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9904287,0.0001595641,0.0002445191,0.001618178,0.00002535406,0.00002501274,0.00007235675,0.00003279714,0.007393463],"genre_scores_gemma":[0.9985342,0.0001190353,0.0001322479,0.000172851,0.00002375323,0.00002239163,0.00005081825,0.00001145577,0.0009331931],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02555414,"threshold_uncertainty_score":0.05081081,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03567885725158383,"score_gpt":0.251923815769703,"score_spread":0.2162449585181191,"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."}}