{"id":"W4405828758","doi":"10.1080/10803548.2024.2418688","title":"On the potential benefits of wide dynamic range compression for workers in loud environments: a scoping literature review","year":2024,"lang":"en","type":"article","venue":"International Journal of Occupational Safety and Ergonomics","topic":"Hearing Loss and Rehabilitation","field":"Neuroscience","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"École de Technologie Supérieure; Institut de recherche Robert-Sauvé en santé et en sécurité du travail; Université du Québec","funders":"Fonds de recherche du Québec – Nature et technologies; Institut de Recherche Robert-Sauvé en Santé et en Sécurité du Travail","keywords":"Hearing loss; Loudness; Limiting; Perception; Speech perception; Intelligibility (philosophy); Industrial noise; Noise (video); Computer science; Audiology; Noise-induced hearing loss; Speech recognition; Noise exposure; Psychology; Engineering; Medicine; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":true,"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":[0.00510959,0.001175811,0.002639519,0.01371202,0.0007738261,0.003343239,0.001342519,0.00228803,0.00605417],"category_scores_gemma":[0.02434461,0.0006653113,0.003261237,0.01110993,0.001079892,0.002524402,0.00162956,0.001377691,0.0008785534],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0017871,"about_ca_system_score_gemma":0.01056585,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005949992,"about_ca_topic_score_gemma":0.01239666,"domain_scores_codex":[0.9976975,0.0005400372,0.0009070395,0.000208362,0.0005320002,0.0001150978],"domain_scores_gemma":[0.9755232,0.01925576,0.00222847,0.0002235956,0.002557102,0.0002117587],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"systematic_review","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001337662,0.0000622188,0.0007117547,0.6066229,0.0009971827,0.0002573647,0.0007599428,0.0002479039,0.0004567748,0.001550061,0.004887967,0.3833122],"study_design_scores_gemma":[0.00002516185,0.0001448875,0.002286495,0.9038039,0.005974083,0.0006304244,0.0009340449,0.00008239192,0.000318091,0.0009624776,0.08480289,0.00003512579],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0004820848,0.9978496,0.000182113,0.0004720605,0.0001261071,0.000059593,0.00008660764,0.000004964921,0.0007369091],"genre_scores_gemma":[0.002559188,0.9965854,0.0002940218,0.0002686449,0.00006623979,0.00006227325,0.00006027532,0.000002461228,0.0001014731],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.01371202,"threshold_uncertainty_score":0.02702242,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02340599711066318,"score_gpt":0.3154731264740862,"score_spread":0.292067129363423,"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."}}