{"id":"W4243444149","doi":"10.32920/ryerson.14648130","title":"Virtual Human Factors Tools for Proactive Ergonomics: Qualitative Exploration And Method Development","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Human-Automation Interaction and Safety","field":"Psychology","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Flexibility (engineering); Context (archaeology); Computer science; Presentation (obstetrics); Motion capture; Human–computer interaction; Human factors and ergonomics; Graphics; Motion (physics); Knowledge management; Process management; Systems engineering; Engineering; Artificial intelligence; Poison control","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":[0.05872582,0.00104242,0.0009678519,0.003420966,0.00473538,0.005888369,0.002504132,0.001475785,0.006438896],"category_scores_gemma":[0.05459953,0.0008528644,0.000682675,0.003311014,0.006806023,0.00393069,0.00653392,0.001554069,0.0006662885],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.008061473,"about_ca_system_score_gemma":0.01772574,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00449019,"about_ca_topic_score_gemma":0.007595575,"domain_scores_codex":[0.9604368,0.03402129,0.001045806,0.0009918351,0.002194635,0.001309675],"domain_scores_gemma":[0.9286672,0.06251288,0.001967349,0.001807344,0.004320536,0.0007246678],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.0003032516,0.0007048781,0.004626761,0.005193679,0.00003113044,0.0006447287,0.7833212,0.001065444,0.003346076,0.03930984,0.002817128,0.1586358],"study_design_scores_gemma":[0.000280531,0.0007288175,0.00326767,0.006511888,0.00005581359,0.0003596824,0.9139112,0.001731763,0.00505598,0.01806109,0.04996119,0.00007442929],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.6702314,0.004206385,0.2195539,0.006551498,0.0004468873,0.04908027,0.002253247,0.0002076146,0.04746878],"genre_scores_gemma":[0.7394518,0.002949922,0.1633209,0.00122415,0.00003638034,0.08062212,0.000379803,0.0001346864,0.01188017],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.05872582,"threshold_uncertainty_score":0.3105755,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2592144776950634,"score_gpt":0.5006554483344278,"score_spread":0.2414409706393644,"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."}}