{"id":"W2119821740","doi":"10.1148/radiol.2503080257","title":"Hemorrhagic Transformation of Ischemic Stroke: Prediction with CT Perfusion","year":2009,"lang":"en","type":"article","venue":"Radiology","topic":"Acute Ischemic Stroke Management","field":"Medicine","cited_by":165,"is_retracted":false,"has_abstract":true,"ca_institutions":"Lawson Health Research Institute; Grey Nuns Community Hospital; Western University; Sunnybrook Health Science Centre","funders":"","keywords":"Medicine; Odds ratio; Confidence interval; Perfusion scanning; Perfusion; Stroke (engine); Magnetic resonance imaging; Internal medicine; Logistic regression; Tissue plasminogen activator; Cerebral blood flow; Prospective cohort study; Nuclear medicine; Receiver operating characteristic; Cardiology; Radiology","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0001079244,0.0001059257,0.0002503169,0.0001091228,0.00002301045,0.000001811342,0.00005633928,0.00005341577,0.00009652797],"category_scores_gemma":[0.00001492965,0.00008028889,0.00004966139,0.0001041001,0.00005542996,0.00007195487,0.000006397274,0.0001328887,0.0000105287],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006398332,"about_ca_system_score_gemma":0.00002965176,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005472009,"about_ca_topic_score_gemma":4.363192e-7,"domain_scores_codex":[0.9992855,0.00001895136,0.0002302542,0.0001591227,0.0001430976,0.0001631167],"domain_scores_gemma":[0.9996138,0.00001616829,0.00008139107,0.0001971556,0.0000426558,0.00004885913],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001307935,0.0002395191,0.01713497,0.0001655282,0.0001406443,0.00007333991,0.0008357369,0.0001341416,0.8387982,0.0002912824,0.07102354,0.06985522],"study_design_scores_gemma":[0.01722114,0.01151371,0.2014512,0.0003611296,0.001279392,0.009040996,0.001423811,0.01551663,0.5703125,0.00003745257,0.1712634,0.0005786043],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.924729,0.0001617095,0.005356646,0.001506128,0.00006059225,0.0003270337,0.000009611802,0.00006235336,0.06778686],"genre_scores_gemma":[0.9967728,0.00008988684,0.001784398,0.0003471727,0.0000922782,0.000007135011,0.0000986502,0.000007552448,0.0008001028],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2684856,"threshold_uncertainty_score":0.3274086,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00679969530337249,"score_gpt":0.2248701127569836,"score_spread":0.2180704174536111,"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."}}