{"id":"W3085441353","doi":"10.1177/0018720820951349","title":"Assessment of Joint Angle and Reach Envelope Demands Using a Video-Based Physical Demands Description Tool","year":2020,"lang":"en","type":"article","venue":"Human Factors The Journal of the Human Factors and Ergonomics Society","topic":"Ergonomics and Musculoskeletal Disorders","field":"Psychology","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"Mitacs","keywords":"Computer science; Motion capture; Task (project management); Standardization; Joint (building); Motion (physics); Artificial intelligence; Simulation; Computer vision; 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":[0.001266555,0.0006177236,0.0002908095,0.002046836,0.0001901822,0.0005698992,0.0006433293,0.0004384285,0.002637442],"category_scores_gemma":[0.003946981,0.0002079586,0.0003549933,0.0008887271,0.000244237,0.0005598835,0.0005495936,0.0002581058,0.0006376462],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003560272,"about_ca_system_score_gemma":0.0006125389,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003022663,"about_ca_topic_score_gemma":0.006801792,"domain_scores_codex":[0.9990473,0.0002364876,0.00009882143,0.0002033732,0.0003723952,0.00004154529],"domain_scores_gemma":[0.9971598,0.0009427315,0.0005641902,0.0002035032,0.001003725,0.0001260963],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.00137028,0.0005554268,0.2038748,0.001498712,0.0002013392,0.0003391279,0.001170207,0.006813966,0.2556432,0.0006605279,0.002154548,0.5257179],"study_design_scores_gemma":[0.0001584224,0.002923061,0.8275782,0.0003440926,0.0002231584,0.001794533,0.001520127,0.06999165,0.0890084,0.0006302187,0.005616831,0.0002112476],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6394191,0.0004486644,0.3508789,0.00009341614,0.00006429227,0.001053914,0.002806424,0.0007467767,0.004488555],"genre_scores_gemma":[0.6898694,0.0004534253,0.3053247,0.00008802743,0.00003754591,0.001023586,0.001452705,0.00006144994,0.001689049],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003022663,"threshold_uncertainty_score":0.008823156,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06479656044834518,"score_gpt":0.3086048953521956,"score_spread":0.2438083349038504,"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."}}