{"id":"W2976278246","doi":"","title":"Medical Imaging Trends in the U.S.","year":2019,"lang":"en","type":"article","venue":"","topic":"Radiation Dose and Imaging","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Magnetic resonance imaging; Medical imaging; Medicine; Computed tomography; Nuclear medicine; Radiology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005484868,0.0002393806,0.0001634229,0.003032067,0.0005572169,0.00129843,0.0003396521,0.0007639381,0.01044249],"category_scores_gemma":[0.004124697,0.0001928046,0.0003216018,0.005448841,0.0003890512,0.001048122,0.0005474563,0.001241002,0.003272139],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004725594,"about_ca_system_score_gemma":0.005033844,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.2451309,"about_ca_topic_score_gemma":0.3864367,"domain_scores_codex":[0.9991845,0.00007108838,0.0001322204,0.0001227003,0.0003548113,0.0001345686],"domain_scores_gemma":[0.9954094,0.0003675956,0.001320523,0.00006410697,0.00208749,0.0007508664],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001960838,0.0001572705,0.3568803,0.0006477957,0.0000605695,0.0003572502,0.0009439787,0.0006368015,0.001326323,0.007935149,0.3381967,0.2926619],"study_design_scores_gemma":[0.0000201177,0.0001378056,0.5789601,0.001119504,0.00005444742,0.001639238,0.002094632,0.0009257918,0.00109485,0.0009450829,0.4129665,0.00004198192],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.3858062,0.1257906,0.002396228,0.1987693,0.003334514,0.000109854,0.06014807,0.001558112,0.2220871],"genre_scores_gemma":[0.7422885,0.1194988,0.006952709,0.03712502,0.002585304,0.0001084238,0.03546838,0.0002566089,0.05571606],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2451309,"threshold_uncertainty_score":0.4874082,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008210773316481216,"score_gpt":0.2972167675596039,"score_spread":0.2890059942431226,"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."}}