{"id":"W4414909970","doi":"10.1177/15910199251369147","title":"Visual Alberta stroke program early computed tomography score versus RAPID-AI perfusion in predicting outcome after late-window thrombectomy","year":2025,"lang":"en","type":"article","venue":"Interventional Neuroradiology","topic":"Acute Ischemic Stroke Management","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computed tomography; Modified Rankin Scale; Logistic regression; Stroke (engine); Perfusion; Computed tomography angiography; Perfusion scanning; Receiver operating characteristic; Occlusion","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002240943,0.0003238035,0.0005985582,0.0007746393,0.00005942151,0.00003709552,0.0002526472,0.0002105386,0.0003710419],"category_scores_gemma":[0.0002074682,0.0003075301,0.0005139032,0.0005419455,0.0002101992,0.0001188997,0.0003773106,0.0006812667,0.00003434001],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001272797,"about_ca_system_score_gemma":0.00005422131,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002239433,"about_ca_topic_score_gemma":0.0001598348,"domain_scores_codex":[0.997512,0.0001942509,0.0008237445,0.0006829784,0.0002814786,0.0005055806],"domain_scores_gemma":[0.9989761,0.000312562,0.0001566027,0.0003282314,0.0001185608,0.0001079475],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.002163811,0.0008748163,0.9889182,0.0001826566,0.0003351748,0.0002232808,0.00006618746,0.00002131619,0.0009654138,0.000168437,0.001362163,0.004718525],"study_design_scores_gemma":[0.006662226,0.002618705,0.9831473,0.0003448767,0.0001877932,0.00003937455,0.00002956051,0.002320208,0.0002778581,0.00002254412,0.004159587,0.0001899678],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9909194,0.0002427815,0.0003069663,0.002168659,0.001644275,0.001146988,0.00002035295,0.0001622776,0.003388367],"genre_scores_gemma":[0.9961898,0.000005076406,0.0004419215,0.001047087,0.0001585765,0.0002530029,0.0001428798,0.0000312066,0.001730441],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005770918,"threshold_uncertainty_score":0.9999377,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01962261351441081,"score_gpt":0.3247961509864319,"score_spread":0.3051735374720211,"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."}}