{"id":"W4414561767","doi":"10.3390/bioengineering12101033","title":"Attention-Fusion-Based Two-Stream Vision Transformer for Heart Sound Classification","year":2025,"lang":"en","type":"article","venue":"Bioengineering","topic":"Phonocardiography and Auscultation Techniques","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Transformer; Encoder; Architecture; Feature extraction; Feature (linguistics); Information fusion; Sensor fusion","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0001235214,0.0001012975,0.0001485836,0.0002787264,0.00007457059,0.00001921425,0.00003682,0.00006269237,0.000009021639],"category_scores_gemma":[0.00002615639,0.00009359059,0.0002091605,0.000326534,0.00002084873,0.00006262407,0.000002488255,0.00006536198,0.000003082451],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003725229,"about_ca_system_score_gemma":0.00003224426,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005602213,"about_ca_topic_score_gemma":0.000001060519,"domain_scores_codex":[0.9994163,0.000006149799,0.0001819554,0.0001683124,0.00009327701,0.0001340097],"domain_scores_gemma":[0.9996555,0.00005230244,0.00002038231,0.0001438995,0.00008338749,0.00004448319],"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":[0.0001243395,0.0001367176,0.006879027,0.0004352196,0.00008486422,7.604086e-7,0.00003536397,0.0003484756,0.9682321,0.002348232,0.002310148,0.01906476],"study_design_scores_gemma":[0.006647351,0.0006221917,0.2945391,0.001489118,0.0004390847,0.000008887556,0.0002081624,0.1081297,0.5176721,0.001485307,0.06816871,0.0005903231],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1502254,0.0002268094,0.8457441,0.001598119,0.0001955568,0.0007163449,0.0000181246,0.0004042842,0.0008712682],"genre_scores_gemma":[0.9867355,0.00001911052,0.01257277,0.0002078752,0.00005375214,0.0001575785,0.0001048298,0.00001242669,0.0001361707],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8365101,"threshold_uncertainty_score":0.3816513,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01572324744740108,"score_gpt":0.3141346899896251,"score_spread":0.298411442542224,"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."}}