{"id":"W2108660397","doi":"10.1109/tbme.2005.869789","title":"A Robust Method for Heart Sounds Localization Using Lung Sounds Entropy","year":2006,"lang":"en","type":"article","venue":"IEEE Transactions on Biomedical Engineering","topic":"Phonocardiography and Auscultation Techniques","field":"Medicine","cited_by":75,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"","keywords":"Entropy (arrow of time); Heart sounds; Wavelet; Speech recognition; Pattern recognition (psychology); Computer science; Bioacoustics; Wavelet transform; Approximate entropy; Artificial intelligence; Mathematics; Physics; Telecommunications; 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":[0.0008677007,0.0007585388,0.0008289835,0.001544558,0.0002548769,0.0005851285,0.0006956689,0.000726669,0.001087266],"category_scores_gemma":[0.002977891,0.00038717,0.0007018282,0.0006607543,0.0004488585,0.0009549645,0.0006899346,0.0006851932,0.000691027],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002506117,"about_ca_system_score_gemma":0.0004152604,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005313542,"about_ca_topic_score_gemma":0.0007276468,"domain_scores_codex":[0.9993061,0.0001444283,0.00004742479,0.0001403982,0.0003292438,0.00003243015],"domain_scores_gemma":[0.9989632,0.000482402,0.0001368791,0.0001267143,0.0002491262,0.00004164623],"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":[0.0003146069,0.0001056913,0.00283041,0.0003182679,0.0001812941,0.0001779301,0.0001297533,0.02496525,0.250325,0.003025589,0.001964605,0.7156616],"study_design_scores_gemma":[0.00008846907,0.0004403596,0.02219983,0.00006027943,0.0001837075,0.001254129,0.00005806716,0.7813918,0.182026,0.00351745,0.008552512,0.0002273623],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01179166,0.0003586177,0.9866851,0.00004392377,0.00005690813,0.00003049302,0.00006921207,0.0006573895,0.0003067551],"genre_scores_gemma":[0.1790535,0.0004634747,0.818184,0.0000723557,0.0001828466,0.0001191258,0.000305864,0.0001785756,0.001440341],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001544558,"threshold_uncertainty_score":0.004588842,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01692342088196212,"score_gpt":0.2808783607771706,"score_spread":0.2639549398952085,"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."}}