{"id":"W4401596042","doi":"10.51731/cjht.2024.947","title":"Canadian Medical Imaging Inventory 2022–2023: Methods","year":2024,"lang":"en","type":"article","venue":"Canadian Journal of Health Technologies","topic":"Radiation Dose and Imaging","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Descriptive statistics; Medical imaging; Unit (ring theory); Per capita; Jurisdiction; Ranking (information retrieval); Population; Medicine; Medical physics; Geography; Nuclear medicine; Computer science; Environmental health; Statistics; Psychology; Radiology; Political science; Artificial intelligence; Mathematics","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":[0.004167804,0.001426676,0.0009393265,0.01801179,0.003371078,0.005965939,0.004262796,0.0007463593,0.04211735],"category_scores_gemma":[0.01332623,0.0008715193,0.001757866,0.02445055,0.0006877269,0.001445937,0.002365301,0.001663554,0.006032418],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.05136565,"about_ca_system_score_gemma":0.1149525,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9723554,"about_ca_topic_score_gemma":0.9660665,"domain_scores_codex":[0.9938471,0.0003434521,0.0006163305,0.0007132009,0.00363566,0.0008442753],"domain_scores_gemma":[0.9839522,0.0005975756,0.0008447762,0.0005378535,0.01331121,0.0007563633],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000256846,0.0002689936,0.07656325,0.002703794,0.0003266484,0.0003733084,0.001055495,0.005200575,0.0002000199,0.02756622,0.7529775,0.1325074],"study_design_scores_gemma":[0.00008396081,0.00004865182,0.1337038,0.001318765,0.0001937543,0.0001956483,0.001943918,0.004297728,0.0003802805,0.002421979,0.8552525,0.0001589175],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"methods","genre_scores_codex":[0.01280222,0.002103567,0.005756414,0.001992822,0.000269406,0.008260795,0.8950546,0.0004245309,0.07333576],"genre_scores_gemma":[0.1076648,0.004658511,0.04634745,0.001606024,0.0002296007,0.01694012,0.7685705,0.0004737963,0.05350911],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9486343,"threshold_uncertainty_score":0.3726856,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02547437220058187,"score_gpt":0.3759987163988628,"score_spread":0.3505243441982809,"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."}}