{"id":"W6907325105","doi":"10.21227/t2vn-tq74","title":"Shoulder Physiotherapy Activity Recognition 9-Axis Dataset","year":2020,"lang":"en","type":"dataset","venue":"IEEE DataPort","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Sunnybrook Hospital; University of Toronto","funders":"","keywords":"Shoulder girdle; Scapula; Isometric exercise; Rotation (mathematics); External rotation; Activity recognition","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":[0.0008395503,0.004899437,0.001996719,0.002461344,0.0009334823,0.001420422,0.003924363,0.003267092,0.01819078],"category_scores_gemma":[0.002840598,0.0005799311,0.001871208,0.003205264,0.0005457751,0.0009057762,0.001882567,0.001832199,0.03885724],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001383709,"about_ca_system_score_gemma":0.001911547,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03251829,"about_ca_topic_score_gemma":0.06272878,"domain_scores_codex":[0.9986516,0.0002016035,0.0001574014,0.0004049251,0.0003907694,0.0001938321],"domain_scores_gemma":[0.9988368,0.0002195397,0.0000893157,0.0002858252,0.0004078038,0.0001606728],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003369574,0.0002933285,0.002696862,0.001022117,0.0001095974,0.0002025362,0.00003617731,0.001305111,0.0008691812,0.0002260239,0.9743648,0.01853741],"study_design_scores_gemma":[0.001036366,0.0005553656,0.05120305,0.0007659515,0.000271458,0.001480022,0.0003966022,0.01630583,0.006592998,0.00208263,0.9190162,0.0002936014],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.003146386,0.0004306419,0.0006622337,0.0002228971,0.0001656895,0.0001249599,0.9916258,0.001877553,0.00174386],"genre_scores_gemma":[0.002031169,0.00009195493,0.0007518691,0.00006746584,0.00001700379,0.0001601418,0.9958929,0.00003601752,0.0009514994],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.03251829,"threshold_uncertainty_score":0.06465805,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07960521865770535,"score_gpt":0.3665749747456095,"score_spread":0.2869697560879041,"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."}}