{"id":"W4415739209","doi":"10.51731/cjht.2025.1280","title":"CT and MRI Examination Volumes in Canada: National Performance Insights","year":2025,"lang":"","type":"article","venue":"Canadian Journal of Health Technologies","topic":"Radiology practices and education","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Workload; Computed tomography; Rural area; Mri scan; Medical imaging","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":[0.005596033,0.0005031104,0.0006773217,0.005562434,0.002596423,0.003738255,0.002665265,0.0005830409,0.002508262],"category_scores_gemma":[0.02705258,0.0006378581,0.0009378917,0.0204025,0.001705479,0.001784971,0.002249215,0.001687947,0.0004510167],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.09096348,"about_ca_system_score_gemma":0.1293083,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9965868,"about_ca_topic_score_gemma":0.9973041,"domain_scores_codex":[0.9907253,0.0006644256,0.0006530585,0.0008642095,0.005188935,0.001904051],"domain_scores_gemma":[0.9500536,0.004455224,0.005114973,0.001090386,0.0329645,0.006321403],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00007422394,0.00005722114,0.9124498,0.0003959141,0.000164894,0.0001029132,0.001650373,0.001406861,0.0001105575,0.001933001,0.0393682,0.04228593],"study_design_scores_gemma":[0.000008538712,0.00002102793,0.9801721,0.000352146,0.00007882943,0.0000998957,0.002282513,0.001642879,0.0001513358,0.0002959256,0.01484488,0.00004993454],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7116222,0.02841762,0.003122065,0.07209759,0.0004853679,0.0002993899,0.1222352,0.0005639515,0.06115658],"genre_scores_gemma":[0.9599205,0.009296236,0.002573205,0.003199986,0.0001897021,0.0000717662,0.02221285,0.0001445232,0.002391168],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.09096348,"threshold_uncertainty_score":0.6599894,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02132066381088199,"score_gpt":0.2846032752716198,"score_spread":0.2632826114607378,"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."}}