{"id":"W1549674954","doi":"","title":"Adjusting historical noise estimates by accounting for hearing protection use: A probabilistic approach and validation","year":2008,"lang":"en","type":"article","venue":"Canadian acoustics","topic":"Noise Effects and Management","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Heart and Stroke Foundation of Canada","keywords":"Hearing loss; Noise (video); Probabilistic logic; Noise-induced hearing loss; Noise exposure; Audiology; Statistics; Computer science; Mathematics; Medicine; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"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":[0.03936269,0.0008571289,0.0004948225,0.001359491,0.0006774847,0.0009445749,0.001738424,0.0008627973,0.0009246154],"category_scores_gemma":[0.1050698,0.0005317995,0.001484722,0.001334361,0.0006847878,0.0009663159,0.001292503,0.001048918,0.0002274269],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007572832,"about_ca_system_score_gemma":0.001570466,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01558826,"about_ca_topic_score_gemma":0.01153801,"domain_scores_codex":[0.9825782,0.01194412,0.0008732928,0.002124306,0.002223609,0.0002563879],"domain_scores_gemma":[0.9383115,0.04154591,0.004984827,0.01074606,0.004247559,0.0001641439],"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":[0.0007414065,0.0004548076,0.7094206,0.0001804614,0.00120161,0.0001733175,0.00116471,0.1493708,0.001982292,0.00587585,0.0004375707,0.1289967],"study_design_scores_gemma":[0.0001888445,0.001841642,0.5017704,0.0001301287,0.0007072084,0.0004776307,0.0003458091,0.4729764,0.00742726,0.008493011,0.005442501,0.0001992505],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6172652,0.0002037368,0.3791396,0.000168419,0.00004307429,0.000581607,0.0007152773,0.0002859618,0.001597068],"genre_scores_gemma":[0.9081079,0.0001097702,0.09034576,0.00004452676,0.00001467183,0.0003252755,0.0006104168,0.00002959202,0.0004120695],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03936269,"threshold_uncertainty_score":0.2081723,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09936562315505448,"score_gpt":0.3176962775922958,"score_spread":0.2183306544372413,"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."}}