{"id":"W7116860852","doi":"10.2139/ssrn.5948954","title":" Clinical Decision Support Tool for In-Ambulatory Management of Acute Ischemic Stroke: Status Report","year":2025,"lang":"","type":"preprint","venue":"SSRN Electronic Journal","topic":"Acute Ischemic Stroke Management","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"George Brown College","funders":"","keywords":"Workflow; Decision support system; Value proposition; Clinical decision support system; Emergency medical services; Triage; Workload; Interoperability; Emergency department; Stroke (engine)","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003781821,0.0008477669,0.0009202803,0.002577975,0.0003843252,0.002380277,0.0008906289,0.0008951025,0.05884837],"category_scores_gemma":[0.0337326,0.0003352872,0.0005853131,0.001484496,0.000212695,0.001314301,0.00138288,0.0007811308,0.02974133],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004910451,"about_ca_system_score_gemma":0.002141725,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001411724,"about_ca_topic_score_gemma":0.002123841,"domain_scores_codex":[0.9975799,0.0007530877,0.0004841274,0.0001618728,0.0008972337,0.0001237812],"domain_scores_gemma":[0.9775633,0.01359496,0.002447563,0.0008882162,0.003695168,0.001810783],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.002349728,0.0003421645,0.03560129,0.000905849,0.0002099531,0.0003405818,0.0001762069,0.0009314062,0.0007257282,0.001162269,0.5352138,0.4220411],"study_design_scores_gemma":[0.004594525,0.001504645,0.144805,0.003252552,0.0008066155,0.002868197,0.0004787146,0.04516959,0.01441125,0.01691152,0.7648942,0.0003032567],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"methods","genre_scores_codex":[0.1176217,0.007935331,0.07959898,0.03411606,0.003589069,0.005461935,0.4820864,0.08788412,0.1817063],"genre_scores_gemma":[0.4301954,0.005270586,0.1974202,0.00756743,0.003370029,0.007536646,0.285803,0.006791645,0.0560451],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.05884837,"threshold_uncertainty_score":0.1968675,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01862294004158466,"score_gpt":0.3503001703772983,"score_spread":0.3316772303357137,"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."}}