{"id":"W3209631928","doi":"10.32920/ryerson.14657409.v1","title":"Developing human factors metrics and tools to support design and management of production","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Ergonomics and Human Factors","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"Natural Sciences and Engineering Research Council of Canada; Ontario Centres of Excellence","keywords":"Workstation; Computer science; Stakeholder; Knowledge management; Human resources; Process management; Resource (disambiguation); 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":[0.06679717,0.003072763,0.001644596,0.01193547,0.00181395,0.01286731,0.003712596,0.001987828,0.003698819],"category_scores_gemma":[0.1608692,0.001346149,0.001358885,0.00526198,0.00218908,0.01461799,0.005065412,0.002767651,0.001522101],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004966218,"about_ca_system_score_gemma":0.01225301,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004099016,"about_ca_topic_score_gemma":0.003971189,"domain_scores_codex":[0.9457394,0.02652125,0.00570043,0.002817034,0.01792962,0.001292324],"domain_scores_gemma":[0.8381625,0.086546,0.01576794,0.01357303,0.04278276,0.003167694],"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":[0.0001702242,0.0005951908,0.01757875,0.002416181,0.0002710516,0.0002416606,0.01108845,0.02125307,0.007253803,0.04397688,0.01395699,0.8811977],"study_design_scores_gemma":[0.0003236076,0.003736152,0.0456543,0.01567671,0.0007363437,0.001104966,0.03447479,0.1844853,0.04735947,0.1681474,0.4970483,0.001252619],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.03683246,0.00174106,0.9262171,0.004889248,0.0004415507,0.003193748,0.0008705393,0.006517747,0.01929668],"genre_scores_gemma":[0.09276839,0.0008153019,0.9010407,0.0002884408,0.00006526428,0.001720386,0.0009640778,0.0005419445,0.001795508],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.06679717,"threshold_uncertainty_score":0.3532614,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1036744341080043,"score_gpt":0.2731522667115556,"score_spread":0.1694778326035513,"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."}}