{"id":"W2730217998","doi":"10.1007/s11517-017-1675-1","title":"A novel approach for acoustic estimation of neck fluid volume between men and women","year":2017,"lang":"en","type":"article","venue":"Medical & Biological Engineering & Computing","topic":"Phonocardiography and Auscultation Techniques","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Canadian Sleep & Circadian Network; Toronto Rehabilitation Institute; University of Toronto; University Health Network","funders":"Canadian Institutes of Health Research; Natural Sciences and Engineering Research Council of Canada; Mitacs","keywords":"Sound (geography); Airway; Obstructive sleep apnea; Feature selection; Kalman filter; Feature (linguistics); Computer science; Sleep apnea; Medicine; Filter (signal processing); Acoustics; Artificial intelligence; Internal medicine; Surgery; Computer vision","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006112382,0.0001269728,0.0004118977,0.00006531345,0.0001167935,0.00001988297,0.0001522424,0.0001860791,0.000008075167],"category_scores_gemma":[0.001816659,0.00009452262,0.00008771717,0.00006520037,0.0001332267,0.0000375009,0.0001032347,0.0001732162,4.868066e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002200497,"about_ca_system_score_gemma":0.00001947547,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007903222,"about_ca_topic_score_gemma":9.933225e-9,"domain_scores_codex":[0.9990585,0.000008946047,0.0002891946,0.0002254043,0.0001760893,0.0002418079],"domain_scores_gemma":[0.9993246,0.0001603393,0.0001042315,0.00016753,0.00004777269,0.0001955464],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003480263,0.0008188396,0.1543599,0.004054619,0.001089315,0.00002042636,0.002174344,0.03547094,0.1217955,0.001059545,0.0006918741,0.6781166],"study_design_scores_gemma":[0.0008375139,0.0003129793,0.2574134,0.0001806774,0.00003221157,0.00001173416,0.00003171663,0.7401851,0.0007307697,0.00004874686,0.00009995005,0.0001152194],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4070266,0.00004532308,0.5924137,0.00006130979,0.00001964146,0.0001991536,0.000006233971,0.00008657238,0.0001415132],"genre_scores_gemma":[0.8972681,0.00001279051,0.1024569,0.00003351512,0.0001543005,0.00002671737,0.00003211986,0.000008680498,0.000006892696],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7047142,"threshold_uncertainty_score":0.3854521,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02467254971015958,"score_gpt":0.2822632037691851,"score_spread":0.2575906540590255,"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."}}