{"id":"W4251796778","doi":"10.32920/ryerson.14662887","title":"Audio display and environmental sound analysis of diagnostic and therapeutic respiratory sounds","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Music and Audio Processing","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Sound (geography); Computer science; Respiratory sounds; Hidden Markov model; Speech recognition; Sound analysis; Work (physics); Redundancy (engineering); Multimedia; Relevance (law); Human–computer interaction; Medicine; Engineering; Acoustics","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":[0.0003892727,0.0004033095,0.0002940026,0.0008057511,0.0001475018,0.0008086998,0.0003126528,0.0004763778,0.001995572],"category_scores_gemma":[0.001944191,0.0001569716,0.0003524648,0.0004856375,0.0003085577,0.00065458,0.0005586026,0.0003324857,0.0006825058],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001566214,"about_ca_system_score_gemma":0.0002598597,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005305315,"about_ca_topic_score_gemma":0.0005359238,"domain_scores_codex":[0.9995329,0.00009746863,0.00002037778,0.00008476681,0.0002243247,0.00004013559],"domain_scores_gemma":[0.9993665,0.0002981938,0.00008038493,0.00006505544,0.0001585262,0.0000312946],"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":[0.0006538839,0.0001721369,0.005757646,0.0003352971,0.00006743892,0.0005047976,0.0003237808,0.03608666,0.360348,0.0054473,0.0009558933,0.5893471],"study_design_scores_gemma":[0.00007207378,0.0008563436,0.05441708,0.00007644717,0.0001240836,0.001514846,0.0004476444,0.7415368,0.1792359,0.007351295,0.01427477,0.0000927033],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1965247,0.0007861676,0.7931045,0.0002636523,0.0001320308,0.0001172771,0.0003154997,0.0013814,0.007374786],"genre_scores_gemma":[0.7970353,0.000566653,0.1970438,0.000103833,0.0002022613,0.00006178318,0.0003012203,0.0001080606,0.004576971],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.001995572,"threshold_uncertainty_score":0.006675839,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.020861125648744,"score_gpt":0.2517764692571445,"score_spread":0.2309153436084005,"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."}}