{"id":"W2008060214","doi":"10.1016/j.ejor.2014.09.032","title":"Investigating work-related ill health effects in optimizing the performance of manufacturing systems","year":2014,"lang":"en","type":"article","venue":"European Journal of Operational Research","topic":"Occupational Health and Safety Research","field":"Health Professions","cited_by":37,"is_retracted":false,"has_abstract":false,"ca_institutions":"Toronto Metropolitan University","funders":"Workplace Safety and Insurance Board","keywords":"Risk analysis (engineering); Work (physics); Markov chain; Computer science; Risk factor; Operations management; Business; Medicine; Economics; Engineering","routes":{"ca_aff":true,"ca_fund":true,"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":[0.001399475,0.0004220132,0.000278406,0.0003395616,0.0003335728,0.0004954828,0.0003294491,0.0004539902,0.001674519],"category_scores_gemma":[0.004619255,0.0001584469,0.0006571681,0.0002691651,0.0003165618,0.0003481688,0.0004463864,0.0003140087,0.0001377463],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005424537,"about_ca_system_score_gemma":0.0006972243,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005062037,"about_ca_topic_score_gemma":0.007289039,"domain_scores_codex":[0.9992944,0.000428929,0.00003246059,0.00004896026,0.00007458268,0.0001207353],"domain_scores_gemma":[0.9972265,0.001510309,0.0007130214,0.0001271657,0.0002254467,0.0001975456],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.01650427,0.01658459,0.8467188,0.0005985703,0.000966706,0.0004012018,0.001559174,0.0203328,0.02905994,0.0004839106,0.0002017939,0.06658822],"study_design_scores_gemma":[0.0001820255,0.02886008,0.9466527,0.00006022295,0.0006725735,0.00008173194,0.001759642,0.01080846,0.01016041,0.000375048,0.0003620048,0.00002494515],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9996208,0.00007561532,0.000109292,0.00002107935,0.000001785723,0.00001235459,0.00001915077,0.000001145624,0.0001387562],"genre_scores_gemma":[0.9995882,0.00005061812,0.0001894509,0.000008508693,0.000002410086,0.00001116039,0.00001986621,6.459921e-7,0.00012912],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005062037,"threshold_uncertainty_score":0.01006514,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1301554391016926,"score_gpt":0.4575596162688259,"score_spread":0.3274041771671333,"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."}}