{"id":"W2284500493","doi":"","title":"Application of Text-Based Methods of Analysis to Symbolic Music","year":2013,"lang":"en","type":"article","venue":"Library and Archives Canada (Government of Canada)","topic":"Music and Audio Processing","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Symbolic data analysis; Natural language processing; Artificial intelligence; Theoretical computer science","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":[0.00002135024,0.00009686454,0.0002595537,0.0000632635,0.00005701568,0.00001526454,0.0004004937,0.0000134475,0.00002094293],"category_scores_gemma":[0.000003468197,0.00008863271,0.00003568974,0.0004630106,0.00004158042,0.0002710434,0.0001305811,0.00004204216,2.126694e-9],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000002973087,"about_ca_system_score_gemma":0.0006917859,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005151275,"about_ca_topic_score_gemma":0.003080813,"domain_scores_codex":[0.9985407,0.0000570743,0.0002811534,0.0002049419,0.0007657374,0.0001504132],"domain_scores_gemma":[0.9991407,0.0001927907,0.0002165537,0.0002986273,0.000001822206,0.000149457],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00004424046,0.00006445296,0.02585829,0.000349438,0.00029094,0.000002806357,0.0003984788,0.002616842,0.3096531,0.1390766,0.0008118031,0.520833],"study_design_scores_gemma":[0.000185646,0.00005249547,0.1371758,0.00004835882,0.00006672129,5.145583e-7,0.0003296249,0.2068642,0.649802,0.002585202,0.002680626,0.00020888],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07329643,0.00009517472,0.8912062,0.004119997,0.00004927827,0.0001969401,0.00002196096,0.000009528229,0.03100447],"genre_scores_gemma":[0.8844894,0.000002624557,0.1137658,0.001433545,0.000009220485,0.00001011769,0.000001280813,0.000004339807,0.0002837083],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8111929,"threshold_uncertainty_score":0.7787222,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004567112357341209,"score_gpt":0.1794739504813065,"score_spread":0.1749068381239653,"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."}}