{"id":"W4312298943","doi":"10.1007/978-3-031-20980-2_26","title":"Harnessing Uncertainty - Multi-label Dysfluency Classification with Uncertain Labels","year":2022,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Music and Audio Processing","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Certainty; Computer science; Artificial intelligence; Machine learning; Uncertain data; Data mining; Mathematics","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":[0.002174923,0.00150689,0.001688561,0.001655649,0.0007392023,0.002208545,0.001755309,0.002094659,0.001508505],"category_scores_gemma":[0.007697417,0.0004085627,0.001208036,0.001416396,0.0007208621,0.002840642,0.002799067,0.002157151,0.0009611712],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006192204,"about_ca_system_score_gemma":0.0007868854,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004188978,"about_ca_topic_score_gemma":0.004248519,"domain_scores_codex":[0.9984609,0.0003485409,0.0001104224,0.0004719162,0.0003961946,0.0002119284],"domain_scores_gemma":[0.9939219,0.004239915,0.0003996633,0.000552971,0.0007194118,0.0001661556],"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":[0.0009076012,0.0003721862,0.0105964,0.000316574,0.0003532621,0.0005591969,0.0004419795,0.09892577,0.02038611,0.007554999,0.01245994,0.8471259],"study_design_scores_gemma":[0.00001120141,0.00005905432,0.001662855,0.00002647119,0.0000625098,0.0000860714,0.00008095714,0.9729581,0.004689564,0.0191887,0.001142615,0.0000317995],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09760565,0.002224338,0.8906811,0.001212996,0.0004328732,0.00009088268,0.001234475,0.00268579,0.003831819],"genre_scores_gemma":[0.8395066,0.0006479336,0.1508335,0.0004905429,0.0006052011,0.0001308875,0.002962259,0.0002388926,0.004584269],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004188978,"threshold_uncertainty_score":0.01150227,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04531384017437876,"score_gpt":0.2778400262541542,"score_spread":0.2325261860797754,"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."}}