{"id":"W3091907035","doi":"10.1109/trpms.2020.3029038","title":"Using Medical Imaging Effective Dose in Deep Learning Models: Estimation and Evaluation","year":2020,"lang":"en","type":"article","venue":"IEEE Transactions on Radiation and Plasma Medical Sciences","topic":"Medical Imaging Techniques and Applications","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University Medical Centre; Toronto Metropolitan University; McMaster University; Vector Institute","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Estimation; Computer science; Deep learning; Artificial intelligence; Medical physics; Machine learning; Medicine; Engineering; Systems engineering","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001451104,0.0001125798,0.0001817419,0.0001585455,0.0002614603,0.0000418079,0.00007066086,0.0001123716,0.0002546185],"category_scores_gemma":[0.0004311018,0.00009360605,0.00002882359,0.0004906396,0.0003564429,0.0002367689,0.000002997305,0.00046911,0.000003786725],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006004468,"about_ca_system_score_gemma":0.0002100889,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009091132,"about_ca_topic_score_gemma":0.00001989776,"domain_scores_codex":[0.9979068,0.0001670311,0.0002729656,0.0003502083,0.001124936,0.0001780263],"domain_scores_gemma":[0.9989488,0.0003832641,0.00006058999,0.00005404127,0.00003560409,0.0005177501],"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":[0.0000328986,0.00007475154,0.0006233724,0.00003498532,0.000007469348,0.000009274553,0.0006261146,0.01680447,0.0001786778,0.0003118424,0.00002339358,0.9812728],"study_design_scores_gemma":[0.001163288,0.0001167972,0.000728733,0.0001551222,0.00004448392,0.000074107,0.0001636188,0.996527,0.0003939798,0.0004316193,0.0001089495,0.00009236821],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3996794,0.0001498306,0.5759659,0.02331523,0.00006256725,0.000482254,0.000001258602,0.00008406258,0.0002594932],"genre_scores_gemma":[0.9924279,0.000432275,0.005601877,0.001406336,0.00004830509,0.00006909655,0.000004334146,0.00000687107,0.00000296138],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9811804,"threshold_uncertainty_score":0.3817144,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07384210317532304,"score_gpt":0.3699477534658936,"score_spread":0.2961056502905706,"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."}}