{"id":"W4401596315","doi":"10.51731/cjht.2024.953","title":"Canadian Medical Imaging Inventory 2022–2023: The Medical Imaging Team","year":2024,"lang":"en","type":"article","venue":"Canadian Journal of Health Technologies","topic":"Radiation Dose and Imaging","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Staffing; Workforce; Medical imaging; Economic shortage; Business; Service delivery framework; Service (business); Medicine; Nursing; Radiology; Marketing; Political science; Government (linguistics)","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":[0.003576448,0.001316,0.0006283248,0.006873175,0.005169472,0.005532535,0.003461561,0.001793336,0.05246812],"category_scores_gemma":[0.01251287,0.001048667,0.001557437,0.008095008,0.0008308392,0.001332672,0.002226896,0.002263214,0.01267022],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.09114623,"about_ca_system_score_gemma":0.3060264,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.982312,"about_ca_topic_score_gemma":0.9841224,"domain_scores_codex":[0.9900361,0.0003023478,0.0003119388,0.0003434515,0.007271968,0.001734054],"domain_scores_gemma":[0.9655934,0.0008185311,0.001010894,0.000507657,0.02459065,0.007478838],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.00007016158,0.0000278442,0.003917505,0.0001820242,0.00002463145,0.00005724914,0.0000777347,0.000309506,0.0002364575,0.003213388,0.9567992,0.03508423],"study_design_scores_gemma":[0.00002819042,0.00002406174,0.0253321,0.0001771735,0.00002157312,0.00008930713,0.0001716881,0.0006063169,0.0002204602,0.000322823,0.9729655,0.00004068653],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.01566984,0.009029157,0.005064053,0.05094953,0.006182181,0.002230585,0.3238264,0.004182632,0.5828657],"genre_scores_gemma":[0.1279842,0.0146827,0.02672817,0.02284206,0.001670067,0.001836131,0.3587442,0.001745349,0.4437671],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9088538,"threshold_uncertainty_score":0.6613153,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01253575170695439,"score_gpt":0.299337682900745,"score_spread":0.2868019311937907,"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."}}