{"id":"W4409603794","doi":"10.61091/jcmcc127b-210","title":"A Modeling Study of Music and Dance Rhythm Matching Using Time Series Analysis","year":2025,"lang":"en","type":"article","venue":"Journal of Combinatorial Mathematics and Combinatorial Computing","topic":"Music and Audio Processing","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Rhythm; Dance; Series (stratigraphy); Matching (statistics); Computer science; Art; Speech recognition; Visual arts; Mathematics; Statistics; Aesthetics; Geology","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001636547,0.000265321,0.00109471,0.0005506848,0.0003943603,0.0003980807,0.0005285607,0.00009730103,0.000001341508],"category_scores_gemma":[0.0001625149,0.0002410828,0.0001476708,0.001277392,0.00006090532,0.0006236515,0.0006275669,0.0003341332,1.355261e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005101148,"about_ca_system_score_gemma":0.0001675927,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003195985,"about_ca_topic_score_gemma":9.76341e-7,"domain_scores_codex":[0.9974605,0.0001323206,0.00128675,0.0002996481,0.000554175,0.0002665408],"domain_scores_gemma":[0.9977008,0.0003121359,0.001021623,0.0003228912,0.0005397086,0.0001028793],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001579478,0.002166999,0.00102315,0.001079422,0.002329958,0.00008189031,0.0280863,0.03364809,0.003634607,0.9208435,0.00003029559,0.006917842],"study_design_scores_gemma":[0.002208756,0.0003516399,0.00005620786,0.0005079834,0.0005109171,0.00005722017,0.001157188,0.6866196,0.0002065413,0.3080978,0.000006320249,0.0002198134],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6921731,0.000271474,0.3053185,0.00004309834,0.001942881,0.0001308522,2.921086e-7,0.00002019741,0.00009956527],"genre_scores_gemma":[0.9656487,0.00001088639,0.03406995,0.0000211681,0.0002314091,6.498955e-7,1.482916e-7,0.00001216127,0.000004903542],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6529715,"threshold_uncertainty_score":0.983107,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01720763455026689,"score_gpt":0.2651558884557773,"score_spread":0.2479482539055104,"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."}}