{"id":"W2801773295","doi":"10.1121/1.5036222","title":"Acoustical corrections to be used for improved in-ear noise dosimetry measurements","year":2018,"lang":"en","type":"article","venue":"The Journal of the Acoustical Society of America","topic":"Noise Effects and Management","field":"Health Professions","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institut de recherche Robert-Sauvé en santé et en sécurité du travail; École de Technologie Supérieure","funders":"","keywords":"Acoustics; Noise (video); Eardrum; Computer science; Calibration; Hearing protection; Sound pressure; Dosimetry; Attenuation; Hearing loss; Physics; Audiology; Optics; Medicine; 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":[0.002117138,0.001879459,0.001215225,0.00151468,0.0006331562,0.001324334,0.001414268,0.00115622,0.007297667],"category_scores_gemma":[0.009982028,0.0008016629,0.0006532176,0.001132322,0.0004212096,0.0008816074,0.001186448,0.001203097,0.004591954],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004718778,"about_ca_system_score_gemma":0.0009100366,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009234753,"about_ca_topic_score_gemma":0.002076952,"domain_scores_codex":[0.9973758,0.000587803,0.0001920392,0.0005701981,0.001172959,0.0001011974],"domain_scores_gemma":[0.9969308,0.0008124277,0.0003597481,0.000713272,0.001124683,0.00005909081],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0006007976,0.0002901364,0.005176108,0.0009511799,0.0001354924,0.0002079733,0.0006619112,0.005037623,0.7007274,0.00224159,0.00261489,0.281355],"study_design_scores_gemma":[0.00005281616,0.0005482082,0.01626232,0.0001530737,0.0003216981,0.0008240396,0.0002568881,0.01874773,0.9105301,0.001384329,0.05078351,0.0001352263],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04910055,0.001690688,0.937721,0.0002130931,0.0008273988,0.0003672106,0.0005450179,0.00493674,0.004598383],"genre_scores_gemma":[0.1795858,0.002407,0.8085197,0.0002150622,0.0001136126,0.00050179,0.0007197962,0.001418004,0.006519291],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007297667,"threshold_uncertainty_score":0.02441311,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05546889543317821,"score_gpt":0.3846906639545489,"score_spread":0.3292217685213706,"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."}}