{"id":"W2472683635","doi":"10.1145/2948910.2948934","title":"Quantitative Evaluation of Percussive Gestures by Ranking Trainees versus Teacher","year":2016,"lang":"en","type":"preprint","venue":"","topic":"Music Technology and Sound Studies","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Centre for Interdisciplinary Research in Music Media and Technology","funders":"","keywords":"Gesture; Stress (linguistics); Ranking (information retrieval); Set (abstract data type); Computer science; Feature (linguistics); Kinematics; Speech recognition; Artificial intelligence; Natural language processing; Linguistics","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":[0.003696203,0.001129464,0.0008779027,0.002803864,0.0003007382,0.001105428,0.0004208361,0.0008336413,0.002770184],"category_scores_gemma":[0.01269795,0.0001134911,0.0003979485,0.001102979,0.0005090291,0.0007034497,0.0007553232,0.0003811444,0.002133029],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000235608,"about_ca_system_score_gemma":0.0003188021,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009253928,"about_ca_topic_score_gemma":0.001879847,"domain_scores_codex":[0.9942191,0.001855694,0.0005086855,0.001028532,0.001959913,0.0004280331],"domain_scores_gemma":[0.9881925,0.006283025,0.001214105,0.0007067982,0.002437839,0.001165885],"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":[0.006023545,0.001221103,0.2762527,0.001550324,0.0006458171,0.0003396444,0.00163666,0.01027328,0.1221135,0.0004196301,0.006157757,0.573366],"study_design_scores_gemma":[0.0001949608,0.007511351,0.8533414,0.0001352531,0.0003420257,0.001478896,0.004002152,0.07300572,0.05368049,0.0006188219,0.005504706,0.000184318],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9670271,0.001078262,0.02412263,0.00009985651,0.0001263318,0.0001934567,0.001971328,0.0008367559,0.004544318],"genre_scores_gemma":[0.983742,0.0002112186,0.01021762,0.00002472706,0.00007285354,0.000136916,0.002935047,0.00009786383,0.002561779],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003696203,"threshold_uncertainty_score":0.01954764,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08007186775417226,"score_gpt":0.3467673696722934,"score_spread":0.2666955019181212,"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."}}