{"id":"W1955940494","doi":"10.1109/cbms.1994.315988","title":"In vitro and in vivo low frequency acoustic analysis of Bjork-Shiley convexo-concave heart valve opening sounds","year":2002,"lang":"en","type":"article","venue":"","topic":"Phonocardiography and Auscultation Techniques","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; Montreal Clinical Research Institute","funders":"","keywords":"Artificial intelligence; Heart valve; Pattern recognition (psychology); Linear discriminant analysis; In vivo; Naive Bayes classifier; Feature (linguistics); Feature vector; Mathematics; Speech recognition; Computer science; Biomedical engineering; Support vector machine; Engineering; Medicine; Biology; Internal 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00113913,0.0003529241,0.0002925963,0.0003960725,0.0001083005,0.0004014253,0.0001271292,0.0004307463,0.0006303309],"category_scores_gemma":[0.002660084,0.0002045761,0.0001708975,0.0001371808,0.0005088639,0.0002395461,0.0001828753,0.0003112146,0.0002320698],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008022758,"about_ca_system_score_gemma":0.00009167994,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00033117,"about_ca_topic_score_gemma":0.000559162,"domain_scores_codex":[0.9995667,0.000121842,0.00005172742,0.0000973583,0.0001192515,0.0000431022],"domain_scores_gemma":[0.9982769,0.00111919,0.0001798614,0.0001096267,0.0002112074,0.0001032468],"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":[0.0003096736,0.00007623893,0.004089565,0.00006239042,0.00001480498,0.00009504498,0.0000866268,0.0003840694,0.9881119,0.00001783549,0.00003230392,0.006719604],"study_design_scores_gemma":[0.00004022654,0.00532592,0.1512646,0.00002633558,0.00009266519,0.001498806,0.0003075835,0.01224271,0.8283357,0.0001068911,0.0007220053,0.00003659355],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9758588,0.0003083612,0.02318183,0.0000267681,0.00004205273,0.00004621805,0.00008131999,0.00004382983,0.0004109196],"genre_scores_gemma":[0.9701468,0.0003738168,0.02820156,0.00005337381,0.00003350423,0.00005590147,0.0002576362,0.00001662666,0.0008608422],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00113913,"threshold_uncertainty_score":0.006024361,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01508658234735668,"score_gpt":0.2692933607753523,"score_spread":0.2542067784279957,"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."}}