{"id":"W4391445147","doi":"10.1111/jon.13191","title":"Clinical and imaging predictors for hemorrhagic transformation of acute ischemic stroke after endovascular thrombectomy","year":2024,"lang":"en","type":"article","venue":"Journal of Neuroimaging","topic":"Acute Ischemic Stroke Management","field":"Medicine","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Basic and Applied Basic Research Foundation of Guangdong Province; Guangzhou Municipal Science and Technology Project; Jinan University","keywords":"Medicine; Logistic regression; Odds ratio; Confidence interval; Internal medicine; Collateral circulation; Stroke (engine); Incidence (geometry); Multivariate analysis; Cardiology; Cerebral blood flow","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006457991,0.0001585766,0.0004586395,0.0002868973,0.00002242625,0.00004319538,0.0000956635,0.00003496738,0.00002142832],"category_scores_gemma":[0.00007246601,0.0001272177,0.0004403853,0.000122562,0.0001140792,0.0004332517,0.00004221619,0.0003976681,0.000001250201],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003404979,"about_ca_system_score_gemma":0.00007496771,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001171536,"about_ca_topic_score_gemma":6.393027e-8,"domain_scores_codex":[0.998337,0.00003172742,0.0008761635,0.0001972849,0.0003564284,0.0002013683],"domain_scores_gemma":[0.9992275,0.0001486223,0.0002035939,0.0001611577,0.0001437575,0.0001153307],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.002137816,0.0003623881,0.3218899,0.005178639,0.005432403,0.00324413,0.002985843,0.00001913257,0.4508511,0.00006689709,0.04435588,0.1634759],"study_design_scores_gemma":[0.02862553,0.002673285,0.283327,0.006699241,0.02644065,0.0262982,0.001915747,0.1124584,0.1364836,0.0001920281,0.3736647,0.001221641],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9656836,0.003020386,0.02613148,0.002846823,0.0006199885,0.0003623282,0.00002434069,0.00003357244,0.001277468],"genre_scores_gemma":[0.9923431,0.0005396868,0.006229059,0.0003795376,0.0003579545,0.000006527341,0.000004095127,0.00003514119,0.0001049039],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3293088,"threshold_uncertainty_score":0.5187789,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0148948160030876,"score_gpt":0.3040322331571462,"score_spread":0.2891374171540586,"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."}}