{"id":"W4384557371","doi":"10.3390/su151411097","title":"Optimizing Human Performance to Enhance Safety: A Case Study in an Automotive Plant","year":2023,"lang":"en","type":"article","venue":"Sustainability","topic":"Occupational Health and Safety Research","field":"Health Professions","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"European Commission; Canadian Institute of Steel Construction","keywords":"Workload; Task (project management); Workstation; Matching (statistics); Automotive industry; Human error; Process (computing); Computer science; Human reliability; Risk analysis (engineering); Reliability (semiconductor); Industrial engineering; Reliability engineering; Production (economics); Systems engineering; Engineering","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002585281,0.0008876278,0.0005292239,0.00106711,0.00164388,0.00138389,0.001709059,0.002659613,0.003152116],"category_scores_gemma":[0.004367526,0.0003213483,0.0007592222,0.0009331466,0.001061587,0.0007407283,0.001316832,0.0009262383,0.0005739664],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001887956,"about_ca_system_score_gemma":0.001599164,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01364486,"about_ca_topic_score_gemma":0.02354473,"domain_scores_codex":[0.9983113,0.0009400969,0.00006125094,0.0001742599,0.0002718133,0.0002412889],"domain_scores_gemma":[0.9947156,0.003769779,0.0002914092,0.0002375572,0.0005498658,0.0004357224],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"case_report","study_design_scores_codex":[0.002816382,0.01465461,0.1188809,0.002603181,0.0003638258,0.02503195,0.01980742,0.6051385,0.02362288,0.01005758,0.005970466,0.1710522],"study_design_scores_gemma":[0.0008652877,0.01725961,0.1213241,0.0005849103,0.0004043072,0.004751301,0.06202307,0.7140899,0.03666625,0.01089325,0.03077449,0.0003635741],"study_design_candidate":"case_report","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9800622,0.0001805722,0.01509289,0.0003031694,0.00002651567,0.0003156705,0.0001963747,0.00005213888,0.003770413],"genre_scores_gemma":[0.9812652,0.000229363,0.01489643,0.00005868069,0.00001470801,0.0001456826,0.0001298355,0.00001939083,0.003240614],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01364486,"threshold_uncertainty_score":0.02713084,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08767742603978472,"score_gpt":0.5393844538167574,"score_spread":0.4517070277769726,"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."}}