{"id":"W2016384300","doi":"10.1121/1.4776933","title":"Adaptive modeling of compression hearing aids: Convergence and tracking issues","year":2003,"lang":"en","type":"article","venue":"The Journal of the Acoustical Society of America","topic":"Hearing Loss and Rehabilitation","field":"Neuroscience","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Computer science; Hearing aid; Adaptive filter; Speech recognition; Distortion (music); Algorithm; Noise (video); Convergence (economics); Acoustics; Artificial intelligence","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":[0.001007753,0.0004170181,0.0003613652,0.0003470415,0.0002477097,0.0005484355,0.0005729778,0.0006662983,0.0006104407],"category_scores_gemma":[0.004279275,0.0002311919,0.0002873849,0.0001824911,0.0004955603,0.0007344445,0.000315365,0.0005486283,0.0002597428],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004368086,"about_ca_system_score_gemma":0.0005590413,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005407395,"about_ca_topic_score_gemma":0.003042328,"domain_scores_codex":[0.9997974,0.00005417054,0.00001479033,0.00002827296,0.00009247776,0.00001290086],"domain_scores_gemma":[0.9990907,0.0005530324,0.00008162539,0.00007011844,0.0001911503,0.00001344115],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0000966532,0.0000391855,0.001588508,0.0001137491,0.00002882747,0.00008227271,0.000213722,0.8645747,0.02304163,0.005663088,0.0002087787,0.1043488],"study_design_scores_gemma":[0.000004024505,0.00002923014,0.0003933668,0.000007801973,0.000004981866,0.00005142172,0.00001092957,0.9931357,0.005149929,0.0009174641,0.0002886618,0.000006448564],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07102571,0.0004011793,0.9264185,0.0001218904,0.00001994847,0.0000558564,0.00001737603,0.0003536973,0.001585889],"genre_scores_gemma":[0.8319214,0.0006534032,0.1642109,0.00006248523,0.00002556563,0.0001646615,0.00005478,0.00005679836,0.00284993],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005407395,"threshold_uncertainty_score":0.01075184,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05326262838953696,"score_gpt":0.3059856163384024,"score_spread":0.2527229879488654,"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."}}