{"id":"W4212885689","doi":"10.32920/ryerson.14665950.v1","title":"Modelling workload to quality using system dynamics in manufacturing and healthcare","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Occupational Health and Safety Research","field":"Health Professions","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Workload; System dynamics; Quality (philosophy); Human factors and ergonomics; Presenteeism; Unit (ring theory); Burnout; Health care; Computer science; Operations management; Risk analysis (engineering); Business; Poison control; Psychology; Medicine; Engineering; Absenteeism; Medical emergency","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":[0.001799739,0.001118431,0.0005945567,0.0009115461,0.0005511261,0.002037366,0.0008627254,0.001482312,0.002413531],"category_scores_gemma":[0.006794764,0.0006495521,0.001207367,0.0008359656,0.001085343,0.00160478,0.001652107,0.001249114,0.0002047857],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001686772,"about_ca_system_score_gemma":0.00172815,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01997425,"about_ca_topic_score_gemma":0.007548284,"domain_scores_codex":[0.9990109,0.000547378,0.00004443241,0.0001307933,0.000157742,0.0001086171],"domain_scores_gemma":[0.9963202,0.002938767,0.000302721,0.0001176421,0.0002240934,0.00009645648],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001463862,0.00002742896,0.001568529,0.00002464766,0.00002502535,0.00002545362,0.00008319251,0.9863505,0.0002705211,0.009497564,0.00008146618,0.002031009],"study_design_scores_gemma":[0.000007682217,0.00002740913,0.0004617622,0.000007463328,0.00000748836,0.000006679731,0.00003287687,0.990665,0.0001147372,0.008173924,0.0004879591,0.00000703418],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2013521,0.0006794112,0.7800773,0.001905335,0.0001935885,0.000192105,0.0003926337,0.0002601502,0.0149473],"genre_scores_gemma":[0.9627555,0.000617346,0.03227673,0.0001469632,0.00007555441,0.0002641997,0.0001330122,0.00004677445,0.003683962],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01997425,"threshold_uncertainty_score":0.03971601,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2986395764987323,"score_gpt":0.5404711828768413,"score_spread":0.241831606378109,"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."}}