{"id":"W32569275","doi":"10.1016/j.acra.2009.10.012","title":"Diagnostic Performance of a Prototype Dual-Energy Chest Imaging System","year":2009,"lang":"en","type":"article","venue":"Academic Radiology","topic":"Digital Radiography and Breast Imaging","field":"Medicine","cited_by":26,"is_retracted":false,"has_abstract":false,"ca_institutions":"Mount Sinai Hospital; Princess Margaret Cancer Centre; University of Toronto; University Health Network","funders":"National Cancer Institute; Health Canada","keywords":"Medicine; Receiver operating characteristic; Radiology; Chest radiograph; Radiography; Nuclear medicine; Digital radiography; Subtraction; Flat panel detector; Image noise; Image quality; Detector; Artificial intelligence; Computer science; Mathematics","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000212752,0.0001684248,0.0004333332,0.0005019966,0.00004028789,0.000004230719,0.0001305425,0.0001382561,0.00001115332],"category_scores_gemma":[0.0001519192,0.0001415108,0.0001078646,0.0006514319,0.0001800996,0.0001753432,0.00001899039,0.0003543524,0.00001692873],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000412243,"about_ca_system_score_gemma":0.00005959921,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001528963,"about_ca_topic_score_gemma":9.318109e-8,"domain_scores_codex":[0.9987715,0.00004150621,0.0004113107,0.000265492,0.0001388024,0.000371416],"domain_scores_gemma":[0.9992592,0.0001769662,0.0001483849,0.0002302066,0.00006003365,0.000125224],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001148903,0.0002367113,0.6150419,0.0009459762,0.0002122525,0.0005006365,0.0005935574,0.00008038993,0.03388542,0.02246068,0.007171255,0.3177224],"study_design_scores_gemma":[0.004127305,0.003828254,0.8940549,0.002844885,0.0004308137,0.03971743,0.0004150672,0.008529547,0.01799209,0.0008163914,0.02645361,0.0007896837],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9785289,0.002921852,0.0001630733,0.001516364,0.0001569713,0.0003647822,0.000004328232,0.0001436662,0.01620009],"genre_scores_gemma":[0.9981452,0.0005566379,0.0001979435,0.0006418145,0.000288683,0.00003845373,0.00001638191,0.00001451753,0.000100391],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3169327,"threshold_uncertainty_score":0.5770643,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007677055296579232,"score_gpt":0.2401645655359494,"score_spread":0.2324875102393702,"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."}}