{"id":"W2803013806","doi":"10.7202/1044669ar","title":"A 3D Camera User Interface for Wrist Angle Monitoring in Piano Performances","year":2016,"lang":"fr","type":"article","venue":"Les Cahiers de la Société québécoise de recherche en musique","topic":"Musicians’ Health and Performance","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Interface (matter); Wrist; Set (abstract data type); Computer vision; Human–computer interaction; Visualization; Tracking (education); Orientation (vector space); Match moving; Artificial intelligence; Simulation; Motion (physics)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001025013,0.001110651,0.0005506499,0.001041091,0.0002831565,0.0007378641,0.001338453,0.001201832,0.03071916],"category_scores_gemma":[0.00272862,0.0004263915,0.000509416,0.0005327422,0.0002828443,0.0007989214,0.001112531,0.0005730412,0.006984888],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002577537,"about_ca_system_score_gemma":0.0003250079,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001586414,"about_ca_topic_score_gemma":0.002193623,"domain_scores_codex":[0.9995195,0.0001187538,0.00003997229,0.0001219742,0.0001667476,0.00003320668],"domain_scores_gemma":[0.9987288,0.0007078215,0.00007024568,0.0001249619,0.0002581986,0.0001098671],"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":[0.00216883,0.0004125057,0.004187175,0.0009385591,0.00009159832,0.002089352,0.001913576,0.003770142,0.2056228,0.00287287,0.08298854,0.6929441],"study_design_scores_gemma":[0.0008970973,0.003092839,0.06269099,0.001194069,0.000500329,0.01003115,0.0008693166,0.2356451,0.2004319,0.005443254,0.4783769,0.0008269359],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03216738,0.0006974544,0.8807797,0.0004091685,0.000240963,0.001351462,0.003151627,0.06413019,0.01707205],"genre_scores_gemma":[0.2267084,0.0006231689,0.7329003,0.0009504665,0.0001400661,0.001836994,0.002602864,0.003641659,0.03059611],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.03071916,"threshold_uncertainty_score":0.1027659,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06737866422067149,"score_gpt":0.4000307507086125,"score_spread":0.332652086487941,"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."}}