{"id":"W4391018190","doi":"10.1016/j.heliyon.2024.e25052","title":"The combination model of serum occludin and clinical risk factors improved the efficacy for predicting hemorrhagic transformation in stroke patients with recanalization","year":2024,"lang":"en","type":"article","venue":"Heliyon","topic":"Acute Ischemic Stroke Management","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Beijing Postdoctoral Science Foundation; Natural Science Foundation of Beijing Municipality; National Natural Science Foundation of China","keywords":"Occludin; Medicine; Internal medicine; Biomarker; Confounding; Prospective cohort study; Stroke (engine); Area under the curve; Observational study; Gastroenterology; Tight junction; Biology","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":[0.0005507124,0.00009222489,0.0001388901,0.00006395778,0.00008242675,0.00002428825,0.00005313689,0.00005531642,0.000001408],"category_scores_gemma":[0.0002088225,0.00004856103,0.00004809357,0.0001310097,0.00004987828,0.0001006056,0.00001746432,0.0001590582,2.484484e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006098576,"about_ca_system_score_gemma":0.00003482716,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001429926,"about_ca_topic_score_gemma":0.00004282614,"domain_scores_codex":[0.9991083,0.00004521181,0.000380324,0.000153614,0.0001891009,0.0001234412],"domain_scores_gemma":[0.9992888,0.0003430498,0.0001206744,0.0001350645,0.00008501888,0.00002740945],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001034869,0.0003323612,0.8965353,0.001462982,0.0003390344,4.828282e-7,0.003652764,0.001607027,0.0003160863,0.0006445837,0.000241867,0.09383264],"study_design_scores_gemma":[0.003057487,0.0005195132,0.2573123,0.0003330252,0.0002920411,3.675218e-7,0.0005953028,0.7367702,0.0008051759,0.00002933219,0.0002211817,0.00006413586],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9767817,0.0001974235,0.02056379,0.0006460795,0.0001106292,0.001400817,0.0000774798,0.0000289052,0.0001931999],"genre_scores_gemma":[0.9990764,0.0003971081,0.0002502068,0.00003294171,0.00002300394,0.00002589569,0.00006182319,0.00001458174,0.0001180638],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7351631,"threshold_uncertainty_score":0.1980262,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01896129691420682,"score_gpt":0.2836176933792725,"score_spread":0.2646563964650657,"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."}}