{"id":"W2467804944","doi":"10.1016/j.jmir.2016.05.003","title":"Knowing the Enemy: Health Care Provider Knowledge of Computed Tomography Radiation Dose and Associated Risks","year":2016,"lang":"en","type":"article","venue":"Journal of medical imaging and radiation sciences","topic":"Radiation Dose and Imaging","field":"Medicine","cited_by":10,"is_retracted":false,"has_abstract":false,"ca_institutions":"Royal University Hospital; University of Saskatchewan","funders":"Ministry of Health, Saskatchewan","keywords":"Medicine; Computed tomography; Health care; Medical radiation; Radiology; Radiation exposure; Abdomen; Radiation dose; Medical physics; Medical imaging; Nuclear medicine","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002222139,0.0001071598,0.0002412615,0.0009207,0.0004955184,0.000960594,0.0004502167,0.001045749,0.005052365],"category_scores_gemma":[0.03751498,0.0003161646,0.0004904409,0.0006873509,0.0005013105,0.001287843,0.0006421079,0.001521014,0.0001967307],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001237772,"about_ca_system_score_gemma":0.001700565,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02830161,"about_ca_topic_score_gemma":0.02918546,"domain_scores_codex":[0.998212,0.0008186448,0.0002086242,0.0001086045,0.0004758706,0.0001763196],"domain_scores_gemma":[0.964298,0.02085563,0.01066342,0.0007722115,0.00171914,0.001691704],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001062283,0.0002707674,0.9872891,0.00005357752,0.00007999565,0.0002209707,0.001361383,0.0001290003,0.00008318643,0.0001902229,0.0008068398,0.009408827],"study_design_scores_gemma":[0.00002805928,0.0001926595,0.9863728,0.0003778782,0.0002302203,0.001760477,0.006453459,0.001950274,0.0001951474,0.0005347016,0.001875543,0.00002880374],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9841704,0.002166962,0.0002459284,0.0056911,0.00003823876,0.00002752848,0.0002868343,0.000006248269,0.00736678],"genre_scores_gemma":[0.9984282,0.0006195435,0.0002778616,0.0003610665,0.00003030924,0.000003571034,0.00005799476,0.000002784213,0.0002186815],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02830161,"threshold_uncertainty_score":0.05627376,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02604800143458993,"score_gpt":0.3655569229963371,"score_spread":0.3395089215617472,"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."}}