{"id":"W2560137806","doi":"","title":"Snare Drum Motion Capture Dataset","year":2015,"lang":"en","type":"article","venue":"New Interfaces for Musical Expression","topic":"Music Technology and Sound Studies","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"","keywords":"Computer science; Drum; Context (archaeology); Artificial intelligence; Motion capture; Motion (physics); Process (computing); Principal (computer security); Computer vision; Baseline (sea); Principal component analysis; Engineering; Geography","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":[0.0008993333,0.001451854,0.001039709,0.002904325,0.0009805968,0.0009622194,0.002560839,0.001722803,0.01459984],"category_scores_gemma":[0.00188678,0.0002355458,0.0009620929,0.002726242,0.0004154156,0.0005982581,0.001606412,0.0008241436,0.01659818],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006938375,"about_ca_system_score_gemma":0.001478811,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01279491,"about_ca_topic_score_gemma":0.04443166,"domain_scores_codex":[0.9988087,0.000128716,0.0001160095,0.000290058,0.0004936284,0.0001629112],"domain_scores_gemma":[0.9990492,0.0001148785,0.00005877611,0.0003029804,0.000390571,0.00008351444],"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":[0.001259555,0.001078471,0.0142791,0.002663256,0.0003821316,0.0007950233,0.0002915436,0.005516791,0.02097685,0.002871156,0.7011576,0.2487285],"study_design_scores_gemma":[0.0003370177,0.001012057,0.1258542,0.000365552,0.0002165341,0.001968374,0.000878215,0.01701248,0.01647087,0.001791896,0.8338856,0.0002071245],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.05307579,0.00153121,0.01517887,0.0003376037,0.0004455135,0.001697226,0.905991,0.005198915,0.01654387],"genre_scores_gemma":[0.01926188,0.0002494231,0.00852642,0.00007976298,0.00005214806,0.0007490327,0.96649,0.00009918317,0.004492217],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.01459984,"threshold_uncertainty_score":0.0488413,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04624808360743828,"score_gpt":0.2925152744008898,"score_spread":0.2462671907934516,"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."}}