{"id":"W3036736862","doi":"10.1097/mao.0000000000002710","title":"Predicting Postoperative Cochlear Implant Performance Using Supervised Machine Learning","year":2020,"lang":"en","type":"article","venue":"Otology & Neurotology","topic":"Hearing Loss and Rehabilitation","field":"Neuroscience","cited_by":42,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; Sunnybrook Health Science Centre","funders":"","keywords":"Mean squared error; Medicine; Cochlear implant; Artificial neural network; Decision tree; Machine learning; Statistics; Artificial intelligence; Algorithm; Audiology; Mathematics; Computer science","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":[0.001813901,0.0005840509,0.0004876853,0.0009455191,0.00015002,0.0004192783,0.0004945262,0.0004177926,0.0007355858],"category_scores_gemma":[0.007595083,0.0001628828,0.0004397631,0.0004724618,0.0001514481,0.0004838092,0.0003396162,0.0004726505,0.0002388537],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003598215,"about_ca_system_score_gemma":0.0006626668,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003324614,"about_ca_topic_score_gemma":0.004092413,"domain_scores_codex":[0.9993901,0.000259553,0.00007100157,0.0001149753,0.0001125835,0.00005172913],"domain_scores_gemma":[0.9957862,0.002491343,0.0006688108,0.0001896871,0.0007341962,0.0001296967],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000883518,0.0008235438,0.6620581,0.000112042,0.0004091683,0.0001381035,0.0001059464,0.1774898,0.002003051,0.000168412,0.001209994,0.1545984],"study_design_scores_gemma":[0.0000345751,0.0004193732,0.08805793,0.00002728821,0.00006443047,0.00009511197,0.00007640551,0.908767,0.001635853,0.0006206094,0.0001807923,0.00002048089],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9656507,0.0002346545,0.03251864,0.0001632102,0.0000246882,0.00006751467,0.0006808846,0.0001613599,0.0004984926],"genre_scores_gemma":[0.9897817,0.00005402395,0.009188365,0.00002276515,0.00001515787,0.00004677515,0.0007275228,0.000004919422,0.0001587764],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003324614,"threshold_uncertainty_score":0.00959295,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05079524055879761,"score_gpt":0.285876686803929,"score_spread":0.2350814462451314,"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."}}