{"id":"W7019511742","doi":"","title":"Generating dance motion using musical features","year":2023,"lang":"en","type":"dissertation","venue":"eScholarship@McGill (McGill)","topic":"Human Motion and Animation","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Centre for Interdisciplinary Research in Music Media and Technology","funders":"","keywords":"Dance; Motion (physics); Animation; Motion capture; Computer animation; Relation (database); Trajectory; Sequence (biology)","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":[0.0003193552,0.001309134,0.0006709513,0.001141859,0.0004283485,0.0006790953,0.0008946285,0.0005995424,0.004845837],"category_scores_gemma":[0.00175487,0.0003204156,0.001192308,0.0007178803,0.0003483594,0.0006951165,0.0009622662,0.0006819229,0.00138133],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003974614,"about_ca_system_score_gemma":0.000418973,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004704372,"about_ca_topic_score_gemma":0.009556953,"domain_scores_codex":[0.999711,0.00003036152,0.00001741118,0.0001442533,0.00006310295,0.00003398044],"domain_scores_gemma":[0.9998065,0.00007474489,0.00001787201,0.00004175132,0.00003676314,0.00002250138],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001001534,0.0002929515,0.006230253,0.0007930719,0.0002394992,0.0003965078,0.0002241524,0.1009804,0.0527031,0.002944433,0.02180484,0.8123893],"study_design_scores_gemma":[0.0002497037,0.0006111392,0.007962112,0.000132555,0.0001525833,0.0005101141,0.0002731205,0.928445,0.02889453,0.004585048,0.02811442,0.00006963552],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3619623,0.00504307,0.5663202,0.0009940455,0.001407047,0.001095581,0.01125532,0.02545783,0.02646459],"genre_scores_gemma":[0.5239069,0.001329991,0.439155,0.0004198385,0.000175718,0.0004307181,0.02132194,0.0008778219,0.01238205],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004845837,"threshold_uncertainty_score":0.01621091,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02427313084383399,"score_gpt":0.2501779004807873,"score_spread":0.2259047696369533,"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."}}