{"id":"W2799367230","doi":"10.1121/1.5035697","title":"Human dissimilarity ratings of musical instrument timbre: A computational meta-analysis","year":2018,"lang":"en","type":"article","venue":"The Journal of the Acoustical Society of America","topic":"Music and Audio Processing","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Timbre; Perception; Computer science; Set (abstract data type); Speech recognition; Waveform; Spectrogram; Correlation; Modulation (music); Pattern recognition (psychology); Mathematics; Artificial intelligence; Musical; Acoustics; Psychology; Telecommunications","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.01200767,0.001124678,0.002409399,0.005729595,0.0006917333,0.004284966,0.002305172,0.001219796,0.002407948],"category_scores_gemma":[0.040929,0.000749973,0.006871281,0.004351657,0.0007862426,0.002132269,0.002051346,0.001503045,0.0002553984],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001559696,"about_ca_system_score_gemma":0.0009637718,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003141572,"about_ca_topic_score_gemma":0.005076047,"domain_scores_codex":[0.9943228,0.003953096,0.0002558459,0.001070372,0.0003282017,0.00006975114],"domain_scores_gemma":[0.9616823,0.0329719,0.001168827,0.003124171,0.0007759682,0.000276889],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"meta_analysis","study_design_scores_codex":[0.003627346,0.0009135584,0.1582822,0.01429507,0.1549993,0.0005603943,0.003137636,0.2402337,0.006902742,0.03657639,0.01179286,0.3686788],"study_design_scores_gemma":[0.0005615054,0.001249562,0.08863226,0.001991386,0.0551808,0.0007322657,0.0008921362,0.6752691,0.00315864,0.1604806,0.01142068,0.0004310688],"study_design_candidate":"meta_analysis","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4712598,0.07299052,0.4332308,0.005146024,0.0003413402,0.0005750237,0.009349358,0.001146334,0.005960777],"genre_scores_gemma":[0.8643437,0.003396926,0.1260733,0.0004881053,0.0000987827,0.0004858065,0.004432412,0.0001810981,0.0004998481],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01200767,"threshold_uncertainty_score":0.06350338,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04623347576107491,"score_gpt":0.2997786854765854,"score_spread":0.2535452097155105,"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."}}