{"id":"W2051597757","doi":"10.1016/j.ssci.2005.09.004","title":"Towards proactive monitoring in the petrochemical industry","year":2005,"lang":"en","type":"article","venue":"Safety Science","topic":"Human-Automation Interaction and Safety","field":"Psychology","cited_by":31,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Petrochemical; Interface (matter); Risk analysis (engineering); Human factors and ergonomics; Graphics; Poison control; Engineering; State (computer science); Computer science; Computer security; Business; Environmental resource management; Environmental science; Environmental engineering; Medical emergency; Medicine","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0008848093,0.00007847774,0.00007362078,0.0001196802,0.0002016687,0.00004644129,0.0005161029,0.00009207329,0.001420056],"category_scores_gemma":[0.0001318203,0.00005683401,0.00003035349,0.0006285532,0.0002572519,0.0003470713,0.00004456557,0.0006073464,0.0004705399],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001948171,"about_ca_system_score_gemma":0.0001000807,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003753783,"about_ca_topic_score_gemma":0.000006657465,"domain_scores_codex":[0.9988034,0.00007418387,0.0002103006,0.0002664416,0.0003693629,0.0002762522],"domain_scores_gemma":[0.9994789,0.00007504952,0.00005468974,0.0002721917,0.00005957244,0.00005956005],"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":[0.0004141676,0.001221997,0.05339056,0.00001102107,0.00004642736,0.00004042536,0.1746515,0.0003424577,0.01921304,0.1502563,0.00528077,0.5951313],"study_design_scores_gemma":[0.0004187498,0.00003214745,0.9493661,0.00001667064,0.000003198363,0.0000548011,0.01080302,0.0004415717,0.005649532,0.0002277742,0.03283763,0.0001488039],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6209055,0.00001790588,0.0003093609,0.005822838,0.0008809753,0.000162682,0.000002422007,0.00005730008,0.371841],"genre_scores_gemma":[0.9978621,0.000001565031,0.000397083,0.0004344467,0.0003318994,0.00002966698,6.362897e-7,0.000003815944,0.0009387733],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8959755,"threshold_uncertainty_score":0.9994928,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03998664879825777,"score_gpt":0.3983359201706168,"score_spread":0.3583492713723591,"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."}}