{"id":"W4411327799","doi":"10.3390/healthcare13121435","title":"Predicting Ischemic Stroke Patients to Transfer for Endovascular Thrombectomy Using Machine Learning: A Case Study","year":2025,"lang":"en","type":"article","venue":"Healthcare","topic":"Acute Ischemic Stroke Management","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University; University of Calgary; University of New Brunswick; Nova Scotia Health Authority; Dalhousie University","funders":"Nova Scotia Health Research Foundation","keywords":"Ischemic stroke; Stroke (engine); Medicine; Cardiology; Ischemia; Engineering","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001322742,0.000678152,0.0005661862,0.001796932,0.001330036,0.0009778538,0.0007593319,0.001377464,0.0007251291],"category_scores_gemma":[0.004882492,0.0004223585,0.0006127365,0.001853249,0.0008240305,0.0005406495,0.0005846666,0.0009376594,0.0002190509],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002327049,"about_ca_system_score_gemma":0.001508832,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04274515,"about_ca_topic_score_gemma":0.0469548,"domain_scores_codex":[0.9992673,0.0002177552,0.0001026394,0.0001192094,0.0001364136,0.0001566281],"domain_scores_gemma":[0.9975547,0.001124061,0.0004235123,0.0002072429,0.0003779372,0.0003125748],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003428934,0.0008425619,0.8670951,0.00009388863,0.0001055296,0.1132341,0.001341308,0.002110189,0.0003312212,0.0003897319,0.00189932,0.01221415],"study_design_scores_gemma":[0.0001974272,0.001798541,0.7221517,0.0003099699,0.0002587432,0.2099404,0.008549488,0.05025846,0.001797121,0.001252771,0.003298195,0.000187131],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9983208,0.0002281302,0.0005301927,0.0002894373,0.000008710243,0.00004361693,0.000165207,0.000005283085,0.0004086452],"genre_scores_gemma":[0.9980608,0.0004376685,0.0008197943,0.00006808584,0.00002812883,0.00002817297,0.0003217171,0.000004293741,0.0002314304],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04274515,"threshold_uncertainty_score":0.08499271,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03354476682860946,"score_gpt":0.336249189413189,"score_spread":0.3027044225845795,"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."}}