{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005208548,0.0007569387,0.0006098903,0.0009879792,0.0004231391,0.0004525071,0.0009734203,0.0006796612,0.001233337],"category_scores_gemma":[0.001582378,0.0001964355,0.0004940562,0.0008296652,0.000284939,0.0006966289,0.000623837,0.0009020757,0.0007333715],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000323945,"about_ca_system_score_gemma":0.0004902469,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004780219,"about_ca_topic_score_gemma":0.003833669,"domain_scores_codex":[0.9996669,0.00004852127,0.00003147073,0.00009732888,0.0001094175,0.00004634212],"domain_scores_gemma":[0.999529,0.0001646664,0.00008515556,0.000079474,0.0001080045,0.00003368849],"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":[0.0004226839,0.0001371073,0.004326428,0.000153947,0.00006110733,0.0003906006,0.0002147661,0.0236393,0.02938369,0.000907546,0.003647747,0.9367151],"study_design_scores_gemma":[0.00003521863,0.0002472491,0.005093275,0.0000309296,0.00004671089,0.0003117645,0.0001925154,0.9642912,0.02401997,0.001891449,0.003796332,0.00004343333],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2742788,0.001370215,0.7052962,0.0006541645,0.0002107278,0.0002201514,0.0004556529,0.0135818,0.003932325],"genre_scores_gemma":[0.7284904,0.0004490267,0.2656612,0.0001463561,0.00007707471,0.00009393306,0.0009105447,0.00006879083,0.00410253],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004780219,"threshold_uncertainty_score":0.009504795,"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."}}