{"id":"W2116479736","doi":"10.1109/cic.2000.898590","title":"Heart sound analysis using the S transform","year":2002,"lang":"en","type":"article","venue":"","topic":"Phonocardiography and Auscultation Techniques","field":"Medicine","cited_by":93,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Computer science; Sound (geography); Acoustics; Speech recognition; Physics","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":[0.0006819366,0.0004608479,0.0003554767,0.002145272,0.0002439326,0.001069665,0.0002573222,0.0005424563,0.004791448],"category_scores_gemma":[0.002207758,0.0001779454,0.0005181404,0.001717743,0.0005319917,0.00104597,0.0005568444,0.0004390709,0.002102832],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001553456,"about_ca_system_score_gemma":0.0004417959,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009837507,"about_ca_topic_score_gemma":0.0006409795,"domain_scores_codex":[0.9996992,0.00006554698,0.00002341973,0.00006470553,0.000123835,0.00002329113],"domain_scores_gemma":[0.9994586,0.0002730699,0.00004889429,0.00007099452,0.0001263182,0.00002217343],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0003754881,0.00007061496,0.004649688,0.0003119079,0.00007490453,0.0003671646,0.0002469191,0.01577842,0.1638056,0.01463335,0.002941624,0.7967443],"study_design_scores_gemma":[0.0001535772,0.001216158,0.03261705,0.0001623537,0.0001853402,0.004237705,0.0005674685,0.6962332,0.1639979,0.03534372,0.06509677,0.0001888872],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08011468,0.001038211,0.9064028,0.0001716844,0.0001469904,0.0001035481,0.0003088973,0.001903616,0.009809591],"genre_scores_gemma":[0.4579504,0.001669958,0.5338019,0.00007907474,0.0001694745,0.00009274762,0.0004915313,0.0002534572,0.005491432],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004791448,"threshold_uncertainty_score":0.01602894,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04610338232781414,"score_gpt":0.3091998907697708,"score_spread":0.2630965084419566,"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."}}