{"id":"W4410135454","doi":"10.1097/aud.0000000000001670","title":"Machine Learning Models Can Predict Tinnitus and Noise-Induced Hearing Loss","year":2025,"lang":"en","type":"article","venue":"Ear and Hearing","topic":"Hearing, Cochlea, Tinnitus, Genetics","field":"Neuroscience","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; University of Lethbridge; Dalhousie University","funders":"","keywords":"Tinnitus; Hearing loss; Audiology; Medicine; Noise-induced hearing loss; Logistic regression; Presbycusis; Population; Noise exposure","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003644078,0.0002398358,0.0002962461,0.0002242078,0.0006185774,0.0002315675,0.0001679694,0.0001289465,0.00001620745],"category_scores_gemma":[0.0003838045,0.0002572119,0.0000427119,0.0003254878,0.0001170487,0.0001607396,0.0005078847,0.0007101534,0.00001066449],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005067172,"about_ca_system_score_gemma":0.00009454328,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001014903,"about_ca_topic_score_gemma":0.0001008405,"domain_scores_codex":[0.9980701,0.0001232858,0.0003092549,0.0006616769,0.0002643011,0.0005714385],"domain_scores_gemma":[0.9992306,0.0001681641,0.00006173606,0.000289505,0.00003586326,0.0002141555],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001533712,0.0001353111,0.3045344,0.000614127,0.00005198227,0.0001704293,0.005776673,0.00797004,0.6165153,0.009407368,0.00009972166,0.05457118],"study_design_scores_gemma":[0.003767737,0.0005130253,0.2169165,0.0009802715,0.0001194834,0.0003297607,0.0005510925,0.5483902,0.2105651,0.004846591,0.01147782,0.00154246],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9854267,0.0004430607,0.0007137037,0.0005376914,0.0001846265,0.0002509209,0.000004877316,0.0002077225,0.01223075],"genre_scores_gemma":[0.9963477,0.0003704837,0.000484206,0.0004737892,0.00008870673,0.000009054882,0.000001516951,0.00003953432,0.002185056],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5404201,"threshold_uncertainty_score":0.999988,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0662510539588161,"score_gpt":0.2861665223076016,"score_spread":0.2199154683487855,"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."}}