{"id":"W3202983345","doi":"10.5853/jos.2021.01312","title":"A Bayesian Framework to Optimize Performance of Pre-Hospital Stroke Triage Scales","year":2021,"lang":"en","type":"article","venue":"Journal of Stroke","topic":"Acute Ischemic Stroke Management","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"Canadian Institutes of Health Research; Alberta Innovates; Freiwillige Akademische Gesellschaft; Canadian Cardiovascular Society; University of Calgary; Wellcome Trust; Wellcome","keywords":"Triage; Medicine; Thrombolysis; Stroke (engine); Acute stroke; Medical emergency; Emergency medicine; Emergency department; Nursing; Myocardial infarction; Internal medicine; Engineering","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0133021,0.001778599,0.00286654,0.001630926,0.0009630664,0.003070276,0.003674956,0.002692,0.006734254],"category_scores_gemma":[0.03948617,0.001727793,0.001059467,0.00165006,0.001730396,0.00301806,0.002200946,0.003577575,0.000962937],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003525172,"about_ca_system_score_gemma":0.005061722,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02688694,"about_ca_topic_score_gemma":0.0221018,"domain_scores_codex":[0.9954789,0.002952254,0.0001556409,0.0004769474,0.0004809042,0.0004553517],"domain_scores_gemma":[0.9760405,0.01884702,0.001190673,0.0005471293,0.002652015,0.0007226882],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001574865,0.00007645135,0.001665769,0.00006406369,0.00007509495,0.00005334747,0.00009024181,0.939674,0.0001822971,0.02984128,0.002520133,0.02559985],"study_design_scores_gemma":[0.00003458435,0.00003260965,0.0003680282,0.00002074237,0.00001479857,0.00001051395,0.00001730543,0.9874104,0.00006272202,0.01147327,0.0005410864,0.00001401181],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02721012,0.0007585033,0.9645737,0.001586956,0.00007547234,0.0002830808,0.0004104397,0.0004077091,0.004694142],"genre_scores_gemma":[0.5614177,0.001069009,0.4268133,0.0005979323,0.0003089274,0.0009345567,0.001251021,0.0002771417,0.007330332],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.02688694,"threshold_uncertainty_score":0.0703491,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008303561518146119,"score_gpt":0.2613030075547524,"score_spread":0.2529994460366063,"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."}}