{"id":"W4387211930","doi":"10.1007/978-3-031-43987-2_29","title":"Interpretable Deep Biomarker for Serial Monitoring of Carotid Atherosclerosis Based on Three-Dimensional Ultrasound Imaging","year":2023,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Cerebrovascular and Carotid Artery Diseases","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"Wilfrid Laurier University","funders":"","keywords":"Interpretability; Biomarker; Computer science; Imaging biomarker; Artificial intelligence; Medicine; Radiology; Magnetic resonance imaging","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":[0.0003437141,0.0007329803,0.0004801372,0.0004733852,0.00007952833,0.0007938766,0.0004643166,0.0005998645,0.002316299],"category_scores_gemma":[0.0006327107,0.0002025678,0.0004700366,0.0003690303,0.000181827,0.0005293341,0.0004867117,0.0004882302,0.00130664],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001598377,"about_ca_system_score_gemma":0.000233294,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005226439,"about_ca_topic_score_gemma":0.001297346,"domain_scores_codex":[0.9998885,0.00001888662,0.000006813488,0.00003272589,0.00003976606,0.00001318071],"domain_scores_gemma":[0.9998751,0.00005783086,0.0000153951,0.00001342585,0.00003017074,0.000008182759],"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":[0.0002622764,0.0001022516,0.003902143,0.0003155897,0.0001322018,0.0003520936,0.00008141145,0.01900676,0.1275776,0.006138591,0.01558653,0.8265425],"study_design_scores_gemma":[0.00003855157,0.0005516099,0.01550986,0.0002434939,0.0004150408,0.002182143,0.0001006091,0.7371713,0.1610152,0.03612516,0.04650914,0.0001379285],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03729136,0.008810618,0.9437484,0.0007701595,0.0005082152,0.00006385074,0.001567453,0.001773284,0.005466725],"genre_scores_gemma":[0.3788489,0.01266304,0.5789486,0.001103229,0.000879588,0.0002241099,0.00347085,0.0004356478,0.02342607],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002316299,"threshold_uncertainty_score":0.007748783,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01959377139219018,"score_gpt":0.2546373870099189,"score_spread":0.2350436156177288,"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."}}