{"id":"W2163844873","doi":"10.1109/wescan.1995.493973","title":"A comparison of neural network models for wheeze detection","year":2002,"lang":"en","type":"article","venue":"","topic":"Phonocardiography and Auscultation Techniques","field":"Medicine","cited_by":41,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"","keywords":"Artificial neural network; Computer science; Wheeze; Speech recognition; Artificial intelligence; Pattern recognition (psychology); SIGNAL (programming language); Fast Fourier transform; Process (computing); Fourier transform; Algorithm; Mathematics; Medicine","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00005773862,0.00005070403,0.0001754463,0.00005274828,0.00003213998,0.000003197988,0.00002239178,0.00004207705,0.00003159272],"category_scores_gemma":[0.000009022682,0.00004145684,0.0001411483,0.0001646664,0.00001986488,0.0000610544,0.000004505453,0.00004568722,9.699704e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000005406276,"about_ca_system_score_gemma":0.000001584252,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008449075,"about_ca_topic_score_gemma":0.000003972951,"domain_scores_codex":[0.9995841,0.000009291482,0.0001612828,0.00008198176,0.00007168987,0.00009169683],"domain_scores_gemma":[0.9997371,0.00003052578,0.00004721401,0.00008648654,0.00006744296,0.00003124982],"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":[0.0008713547,0.001105191,0.0234961,0.0005958359,0.0005113787,0.000002409833,0.002475115,0.0422412,0.07870426,0.006934886,0.09468367,0.7483786],"study_design_scores_gemma":[0.0007944699,0.0006886214,0.001851445,0.00003616706,0.00008591263,0.000005715752,0.0001003642,0.8323525,0.1582233,0.004168541,0.001605729,0.00008715805],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2062961,0.0009741017,0.7746292,0.0002854539,0.0001296831,0.0008553867,0.000004511314,0.0003598632,0.01646571],"genre_scores_gemma":[0.9899299,0.00002789491,0.009567,0.0001186262,0.00007411301,0.00004198069,0.000003352897,0.000006048934,0.0002310417],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7901113,"threshold_uncertainty_score":0.1690561,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07318425768704491,"score_gpt":0.3304401824089654,"score_spread":0.2572559247219205,"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."}}