{"id":"W4409637139","doi":"10.1007/978-3-031-90167-6_12","title":"Towards Human-Quality Drum Accompaniment Using Deep Generative Models and Transformers","year":2025,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Balance, Gait, and Falls Prevention","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Memorial University of Newfoundland","funders":"","keywords":"Computer science; Transformer; Generative grammar; Drum; Artificial intelligence; Electrical engineering; Voltage; Mechanical engineering; Engineering","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":[0.0007049734,0.0009504153,0.0008256764,0.0004118414,0.0002929296,0.001304086,0.001162685,0.001031742,0.007740814],"category_scores_gemma":[0.001863866,0.0006134458,0.001066663,0.0005828606,0.000626581,0.00156156,0.001907259,0.001602763,0.003064462],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004179882,"about_ca_system_score_gemma":0.0004949975,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003105462,"about_ca_topic_score_gemma":0.005231848,"domain_scores_codex":[0.9997076,0.00007831557,0.00001281641,0.00007814846,0.00008875604,0.00003416633],"domain_scores_gemma":[0.9994068,0.0003634001,0.00002602036,0.00009257812,0.00008024762,0.00003093049],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0004585752,0.00009762476,0.0004572462,0.0002580291,0.0001197325,0.000237749,0.0002803429,0.3949219,0.04129771,0.04353792,0.005666652,0.5126666],"study_design_scores_gemma":[0.00001137247,0.00003718074,0.00004483301,0.00001223372,0.00001120731,0.00004041251,0.00002020595,0.9836639,0.004802702,0.009419966,0.001927985,0.000008106237],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.004188755,0.0001886923,0.9925081,0.00004861292,0.0000367021,0.00001672128,0.00006461378,0.001523617,0.001424112],"genre_scores_gemma":[0.3766704,0.0007494633,0.6043081,0.0002081034,0.00009979672,0.0001113811,0.0008006197,0.001006112,0.01604592],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007740814,"threshold_uncertainty_score":0.02589566,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07822942560892267,"score_gpt":0.4014520319203767,"score_spread":0.3232226063114541,"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."}}