{"id":"W4412158966","doi":"10.51731/cjht.2025.1165","title":"Hourly MRI Exam Volumes Across Canada in 2022–2023","year":2025,"lang":"en","type":"article","venue":"Canadian Journal of Health Technologies","topic":"Radiomics and Machine Learning in Medical Imaging","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Environmental science","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":[0.001534836,0.0004661626,0.0004993439,0.002535058,0.002005644,0.002141651,0.001832701,0.0005505644,0.005205594],"category_scores_gemma":[0.009294944,0.0004624837,0.000798305,0.006394974,0.0007615061,0.0008071982,0.00113209,0.001440459,0.0009006737],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.06078181,"about_ca_system_score_gemma":0.06432711,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9947804,"about_ca_topic_score_gemma":0.9955713,"domain_scores_codex":[0.9970276,0.0001730728,0.0001530754,0.0002680336,0.001388933,0.0009892845],"domain_scores_gemma":[0.9885018,0.0005487411,0.001263554,0.0001849038,0.006774149,0.002726796],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003529309,0.00006250745,0.7583411,0.000511189,0.000210885,0.0004778992,0.00166432,0.001787778,0.0005127608,0.001774189,0.1616367,0.07266783],"study_design_scores_gemma":[0.00001992234,0.00002625173,0.9618772,0.0002327528,0.00005119645,0.000278248,0.001820478,0.001206503,0.0002901331,0.0001811233,0.03396053,0.00005563595],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6537834,0.01849592,0.002500137,0.03488775,0.0009964457,0.0002999546,0.246537,0.001256815,0.04124239],"genre_scores_gemma":[0.9393774,0.006455494,0.001858312,0.004419415,0.000205199,0.00011191,0.03682052,0.0002134703,0.01053837],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06078181,"threshold_uncertainty_score":0.441005,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009638817110730492,"score_gpt":0.3077956371914655,"score_spread":0.298156820080735,"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."}}