{"id":"W1652220882","doi":"10.1109/pacrim.2001.953517","title":"New algorithms and technology for analyzing gestural data","year":2002,"lang":"en","type":"article","venue":"","topic":"Music Technology and Sound Studies","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"","keywords":"Gesture; Computer science; Drum; SIGNAL (programming language); Performing arts; Musical instrument; Percussion; Speech recognition; Computer music; Motion capture; Musical; Algorithm; Acoustics; Motion (physics); Artificial intelligence; Engineering; Physics","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":[0.002902225,0.002026271,0.001940242,0.005955748,0.00106712,0.005127872,0.002845184,0.002497692,0.006092969],"category_scores_gemma":[0.01532605,0.00102453,0.002008917,0.005310245,0.002594238,0.007206973,0.002945542,0.002853957,0.00540738],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007512275,"about_ca_system_score_gemma":0.0009433968,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001605714,"about_ca_topic_score_gemma":0.001264537,"domain_scores_codex":[0.9960175,0.000720987,0.0004982336,0.001029878,0.001597382,0.0001360477],"domain_scores_gemma":[0.9938118,0.003137781,0.0004929369,0.001507185,0.0009118359,0.0001383289],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001932976,0.0001005806,0.001758424,0.0007404133,0.0002473154,0.000279767,0.0005502636,0.01804886,0.02262746,0.06851845,0.008050052,0.878885],"study_design_scores_gemma":[0.0001060696,0.0002600591,0.003643675,0.0004146132,0.0001889954,0.001640533,0.0006272019,0.5266634,0.02592472,0.3312972,0.1089745,0.0002588506],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00078688,0.0004841994,0.9967946,0.0001199094,0.00006923306,0.00005209555,0.0001623664,0.0009026882,0.0006280426],"genre_scores_gemma":[0.01353079,0.00110217,0.982307,0.0001833917,0.0001584111,0.0004142076,0.0006428051,0.0002046864,0.001456664],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.006092969,"threshold_uncertainty_score":0.020383,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05558792977928972,"score_gpt":0.2739907971652321,"score_spread":0.2184028673859423,"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."}}