{"id":"W2110273043","doi":"10.1159/000331467","title":"Fluid-Attenuated Inversion Recovery Hyperintensity in Acute Ischemic Stroke May Not Predict Hemorrhagic Transformation","year":2011,"lang":"en","type":"article","venue":"Cerebrovascular Diseases","topic":"Acute Ischemic Stroke Management","field":"Medicine","cited_by":30,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"National Institute of Biomedical Imaging and Bioengineering; National Institute of Neurological Disorders and Stroke; National Medical Research Council; National Health and Medical Research Council; National Stroke Foundation","keywords":"Fluid-attenuated inversion recovery; Medicine; Hyperintensity; Thrombolysis; Stroke (engine); Lesion; Radiology; Intracerebral hemorrhage; Magnetic resonance imaging; Cardiology; Internal medicine; Nuclear medicine; Pathology; Subarachnoid hemorrhage","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001727649,0.0003330518,0.000509972,0.0003194194,0.00006565671,0.00001915007,0.0002223392,0.0001509378,0.0005485035],"category_scores_gemma":[0.0001029566,0.0003098469,0.0004514217,0.0003172305,0.0001100637,0.0003782476,0.000126797,0.000251356,0.0002087238],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002585646,"about_ca_system_score_gemma":0.00009185726,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001742768,"about_ca_topic_score_gemma":0.000006887943,"domain_scores_codex":[0.9979399,0.00006037398,0.0004680103,0.0005378822,0.0005380362,0.00045583],"domain_scores_gemma":[0.9987273,0.00002385284,0.00009977989,0.0007266748,0.0001305464,0.0002918295],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.008376039,0.003125607,0.6091455,0.002582979,0.005639475,0.001160603,0.003024207,0.00008259874,0.1824878,0.0000732087,0.1319348,0.05236709],"study_design_scores_gemma":[0.01437387,0.0006921888,0.6747982,0.0006594596,0.005089872,0.000251707,0.001862466,0.005455669,0.2731307,0.00002401533,0.02251993,0.001141878],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9859242,0.0002852872,0.0007506876,0.0005278287,0.000231142,0.0009217785,0.0001283461,0.0002265609,0.01100411],"genre_scores_gemma":[0.9958628,0.0004705165,0.0008123667,0.001109597,0.00007689247,0.00006379003,0.0005075685,0.00004808408,0.001048385],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1094149,"threshold_uncertainty_score":0.9999354,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01644549675387573,"score_gpt":0.2178343291937156,"score_spread":0.2013888324398399,"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."}}