{"id":"W2208023320","doi":"10.2214/ajr.14.13321","title":"Model-Based Iterative Reconstruction in CT Enterography","year":2015,"lang":"en","type":"article","venue":"American Journal of Roentgenology","topic":"Radiation Dose and Imaging","field":"Medicine","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"Vancouver General Hospital","funders":"","keywords":"Medicine; Iterative reconstruction; Nuclear medicine; Radiology","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":[],"consensus_categories":[],"category_scores_codex":[0.000182418,0.00006936647,0.0002906711,0.0005302666,0.00001124592,0.000006727835,0.0000560617,0.00001111843,0.00001436596],"category_scores_gemma":[0.00006663216,0.00005888326,0.00007956525,0.0002912228,0.000176783,0.0001182838,0.000005758583,0.0001936583,0.000003845665],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009430418,"about_ca_system_score_gemma":0.0002042734,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001877781,"about_ca_topic_score_gemma":0.000006852639,"domain_scores_codex":[0.9992457,0.0000862905,0.0003269316,0.00008241249,0.0001187697,0.0001399191],"domain_scores_gemma":[0.9993044,0.00001980621,0.0003259805,0.00008290271,0.0001392608,0.000127622],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0007156929,0.0001798522,0.7163787,0.000005042574,0.0001223066,0.0002455415,0.0009794058,0.007288563,0.001770678,0.00003738463,0.0006161628,0.2716607],"study_design_scores_gemma":[0.05756926,0.0420575,0.3267789,0.001214994,0.0009427657,0.04619493,0.03428357,0.4348051,0.03284452,0.004904421,0.01704246,0.001361545],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9898111,0.0002208324,0.007046927,0.002209963,0.0001776266,0.00005188849,8.126343e-7,0.000006234716,0.0004746578],"genre_scores_gemma":[0.9929181,0.0000389195,0.005874444,0.001078659,0.00006660035,0.000001461977,0.000001495119,0.000007216976,0.00001311916],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4275165,"threshold_uncertainty_score":0.240119,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02296788366267762,"score_gpt":0.2913792645555964,"score_spread":0.2684113808929188,"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."}}