{"id":"W4403069449","doi":"10.1007/978-3-031-72120-5_2","title":"A Hybrid CNN-Transformer Feature Pyramid Network for Granular Abdominal Aortic Calcification Detection from DXA Images","year":2024,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Electrical and Bioimpedance Tomography","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Manitoba","funders":"","keywords":"Computer science; Artificial intelligence; Transformer; Feature (linguistics); Pattern recognition (psychology); Pyramid (geometry); Calcification; Computer vision; Radiology; Medicine; Electrical engineering; Physics; Engineering; Voltage","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002182842,0.0004443067,0.0003820387,0.000367981,0.0001500348,0.0002222878,0.0004710158,0.000286959,0.00001129632],"category_scores_gemma":[0.00001204901,0.0003791241,0.0002385604,0.0004688727,0.0002586081,0.0001579773,0.00003158477,0.0008234921,0.00001979178],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001693963,"about_ca_system_score_gemma":0.00004795927,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003053949,"about_ca_topic_score_gemma":0.00007925179,"domain_scores_codex":[0.9979572,0.000006683074,0.0003153623,0.0007749948,0.000379485,0.000566264],"domain_scores_gemma":[0.9992006,0.0002003776,0.00005673761,0.0003512408,0.00008882541,0.0001022028],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00003239447,0.00000909269,0.0000136775,0.0001563503,0.00004071502,0.00001984404,0.00006669066,0.06082133,0.009827679,0.0001349554,0.0002441604,0.9286331],"study_design_scores_gemma":[0.0002095737,0.0001570426,0.0001480607,0.0004083394,0.0000866833,0.00002173847,9.289786e-8,0.7459688,0.04447787,0.2032476,0.004611463,0.0006627649],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0007237595,0.005327397,0.9906002,0.0002547248,0.00181335,0.0005433954,0.00006375407,0.0003189378,0.0003544571],"genre_scores_gemma":[0.9419676,0.0004522718,0.05408712,0.0002669296,0.002650654,0.0000753635,0.00009054035,0.0001137812,0.0002957178],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9412439,"threshold_uncertainty_score":0.9998661,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006499355738533365,"score_gpt":0.2092512614040009,"score_spread":0.2027519056654675,"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."}}