{"id":"W2033237937","doi":"10.1145/1841317.1841320","title":"Ancient Chinese zither (guqin) music recovery with support vector machine","year":2010,"lang":"en","type":"article","venue":"Journal on Computing and Cultural Heritage","topic":"Music and Audio Processing","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo; Western University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Notation; Duration (music); Memorization; Computer science; Musical notation; Musicology; Speech recognition; Natural language processing; Visual arts; Musical; Literature; Art; Cognitive psychology; Psychology; Linguistics","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":[0.0003906778,0.0002248594,0.0002306785,0.00005556711,0.0005672561,0.0007301656,0.000382791,0.00006080149,0.00007884362],"category_scores_gemma":[0.00003002502,0.0001243514,0.00007393004,0.0002497172,0.00005970377,0.0005566091,0.000114702,0.0007316186,0.00001881603],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002252551,"about_ca_system_score_gemma":0.00005896943,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006163784,"about_ca_topic_score_gemma":0.0000178877,"domain_scores_codex":[0.9987115,0.000040866,0.00025416,0.0003182888,0.0003286601,0.0003464995],"domain_scores_gemma":[0.9992009,0.00004909888,0.0002181486,0.0002032484,0.0001090176,0.0002195512],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0002549334,0.000624191,0.0207238,0.0001723917,0.0001828175,0.001374752,0.01405253,0.0007185024,0.06669272,0.003238013,0.01866288,0.8733025],"study_design_scores_gemma":[0.01190448,0.008571939,0.5063099,0.002006964,0.0001315896,0.03737608,0.001630297,0.209994,0.004718234,0.003351763,0.208307,0.005697661],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9831298,0.0001333389,0.01196226,0.001099836,0.00117113,0.00006113751,0.000001249719,0.00009571503,0.002345526],"genre_scores_gemma":[0.9813427,0.00000882368,0.01479034,0.002585999,0.0006411952,6.715938e-7,0.000001325264,0.00001289859,0.0006160766],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8676048,"threshold_uncertainty_score":0.7041003,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01089994415786446,"score_gpt":0.2429568997621966,"score_spread":0.2320569556043321,"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."}}