{"id":"W2034283895","doi":"10.1002/sdr.338","title":"Learning from incidents: from normal accidents to high reliability","year":2006,"lang":"en","type":"article","venue":"System Dynamics Review","topic":"Complex Systems and Decision Making","field":"Decision Sciences","cited_by":226,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Reliability (semiconductor); Warning system; Process (computing); Computer science; Incident response; Warning signs; Computer security; Accident (philosophy); Risk analysis (engineering); Engineering; Business; Transport engineering; Telecommunications","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":[0.001226304,0.0003210693,0.0002369012,0.0005257404,0.0004980054,0.001858721,0.0005948387,0.0008866091,0.002764589],"category_scores_gemma":[0.005970389,0.0001780014,0.0002119741,0.0004146263,0.001643508,0.001836828,0.001032831,0.001092506,0.000375572],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001263606,"about_ca_system_score_gemma":0.001251201,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002566184,"about_ca_topic_score_gemma":0.002175674,"domain_scores_codex":[0.9990904,0.0003994121,0.00003629483,0.00009830906,0.0002676646,0.0001079357],"domain_scores_gemma":[0.9976204,0.001256778,0.0003974264,0.000100055,0.0003595221,0.0002657977],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0002900311,0.0004578185,0.02950737,0.001088475,0.0001009496,0.001603906,0.005177934,0.08784989,0.004884142,0.3831558,0.01991379,0.4659699],"study_design_scores_gemma":[0.0001072197,0.0009136101,0.02904668,0.000440805,0.00009829087,0.002063876,0.00830805,0.1221202,0.006157434,0.7586486,0.07197814,0.0001170765],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5859967,0.01502878,0.2194164,0.03231944,0.0003472177,0.0002342681,0.00022038,0.0006229955,0.1458139],"genre_scores_gemma":[0.9831648,0.004609841,0.007924439,0.0004820482,0.00006553205,0.00003272058,0.00005078845,0.00001607696,0.003653685],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002764589,"threshold_uncertainty_score":0.009248435,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04909349486495921,"score_gpt":0.356382589324226,"score_spread":0.3072890944592668,"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."}}