{"id":"W4401596293","doi":"10.51731/cjht.2024.951","title":"Canadian Medical Imaging Inventory 2022–2023: MRI","year":2024,"lang":"en","type":"article","venue":"Canadian Journal of Health Technologies","topic":"Radiation Dose and Imaging","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Institute for Health Information","funders":"","keywords":"Medicine; Population; Magnetic resonance imaging; Nuclear medicine; Medical imaging; Demography; Radiology; Environmental health","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011458,0.0001322197,0.0003293483,0.002213537,0.0002136566,0.00008791714,0.000305055,0.0001561253,0.0007273674],"category_scores_gemma":[0.001019393,0.0001154149,0.0001060161,0.0006550345,0.0001859932,0.0002170376,0.00001329849,0.001101602,0.00008335194],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001747621,"about_ca_system_score_gemma":0.03751214,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.2084472,"about_ca_topic_score_gemma":0.2851348,"domain_scores_codex":[0.9981893,0.00004221246,0.0005827327,0.0001688813,0.000365165,0.0006517561],"domain_scores_gemma":[0.9986578,0.00003876425,0.0001152818,0.0002178696,0.000117142,0.0008531326],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000002085548,0.000003880739,0.01284602,0.0001414608,0.00005106065,0.004080873,0.0002347668,0.000002325585,0.000009822583,0.001070318,0.2225743,0.7589831],"study_design_scores_gemma":[0.0002248063,0.00007011028,0.002766617,0.001021939,0.00001960599,0.003206743,0.002277107,0.00114598,0.00007411963,0.0009187716,0.9881628,0.0001113727],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.01724794,0.3385089,0.0002348545,0.6382221,0.002108414,0.000198665,0.00001903044,0.0001923299,0.003267764],"genre_scores_gemma":[0.9898979,0.002194067,0.0001289805,0.007121266,0.000109426,0.000003627072,0.000005201567,0.00002621709,0.0005133171],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9726499,"threshold_uncertainty_score":0.9679443,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01416932765813073,"score_gpt":0.2982021297440637,"score_spread":0.284032802085933,"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."}}