{"id":"W2080058093","doi":"10.1145/1101149.1101276","title":"The dancing genome project","year":2005,"lang":"en","type":"article","venue":"","topic":"Human Motion and Animation","field":"Engineering","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Montréal; Université de Montréal","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Choreography; Computer science; Movement (music); Process (computing); Motion capture; Convergence (economics); Genetic algorithm; Simple (philosophy); Rate of convergence; Vocabulary; Artificial intelligence; Motion (physics); Human–computer interaction; Computer vision; Dance; Computer graphics (images); Machine learning; Programming language; Key (lock)","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00004270182,0.00002088408,0.00001443115,0.000009677957,0.00004701993,0.0000228373,0.00002730341,0.000006998831,0.00009333458],"category_scores_gemma":[0.000002232277,0.00001340701,0.000008417411,0.00002448343,0.00000297419,0.0000422623,0.000002650919,0.00002391038,0.0002317343],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001638857,"about_ca_system_score_gemma":0.000001750134,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":7.861521e-7,"about_ca_topic_score_gemma":0.00002657735,"domain_scores_codex":[0.9998554,0.000002278657,0.00004164113,0.00002060893,0.00002768261,0.0000524123],"domain_scores_gemma":[0.9999414,0.000005067048,0.000002417778,0.00004041475,0.000003991788,0.000006715452],"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":[0.000003958917,0.00003024975,0.0001998964,0.00006742106,0.00005933957,0.000001548645,0.005715669,0.09391732,0.1558503,0.08946063,0.06854612,0.5861476],"study_design_scores_gemma":[0.00007093608,0.00000419511,0.003378028,0.000002181018,0.000001137758,0.00000139671,0.0001136876,0.1298583,0.00137589,0.00005168878,0.865082,0.00006052775],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.2992618,0.0002970345,0.04223789,0.0005695355,0.0001604307,0.0001822792,6.621311e-7,0.001013643,0.6562767],"genre_scores_gemma":[0.9959372,0.00002058022,0.000623999,0.00004549993,0.0001148433,0.000003013771,7.167083e-7,0.000004610929,0.003249591],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7965359,"threshold_uncertainty_score":0.2978553,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01112043953047541,"score_gpt":0.2132991668025556,"score_spread":0.2021787272720802,"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."}}