{"id":"W2114492537","doi":"10.1016/j.artint.2009.06.001","title":"Probabilistic models for melodic prediction","year":2009,"lang":"en","type":"article","venue":"Artificial Intelligence","topic":"Music and Audio Processing","field":"Computer Science","cited_by":17,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université de Montréal","funders":"","keywords":"Chord (peer-to-peer); Melody; Probabilistic logic; Computer science; Polyphony; Statistical model; Hidden Markov model; Artificial intelligence; Metric (unit); Mathematics; Speech recognition; Machine learning","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":[0.004637908,0.001155521,0.002799019,0.002108532,0.0009468158,0.002858951,0.00453472,0.003411673,0.006247899],"category_scores_gemma":[0.02519318,0.002017935,0.002056011,0.00258801,0.001928928,0.005810749,0.002135909,0.004191552,0.001802352],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001877244,"about_ca_system_score_gemma":0.001144869,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01472372,"about_ca_topic_score_gemma":0.0133291,"domain_scores_codex":[0.9979733,0.0008202529,0.0001496904,0.0005163531,0.0003416348,0.0001987657],"domain_scores_gemma":[0.9799714,0.01686106,0.0008609305,0.001153348,0.0008785658,0.0002746086],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002448199,0.00009631935,0.001708466,0.0001686345,0.0001895797,0.00009145967,0.0001185822,0.8060704,0.0005315957,0.1280659,0.004126635,0.05858755],"study_design_scores_gemma":[0.00001159867,0.000006955622,0.0001667387,0.000008703438,0.00001448006,0.00001528238,0.000004021388,0.9329457,0.00007121924,0.06638741,0.0003556533,0.00001231482],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0173836,0.002515297,0.9752026,0.001233163,0.0001721337,0.00003993789,0.0006476272,0.0008154029,0.001990284],"genre_scores_gemma":[0.8224353,0.004052911,0.1538514,0.0005950398,0.0009309403,0.0004133072,0.002849207,0.000402337,0.01446961],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01472372,"threshold_uncertainty_score":0.02927601,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08764861002211706,"score_gpt":0.2991786291769817,"score_spread":0.2115300191548647,"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."}}