{"id":"W2897633930","doi":"10.1161/str.49.suppl_1.tp275","title":"Abstract TP275: Modelling the Impact of Mobile Stroke Unit Dispatcher Accuracy on Patient Outcomes","year":2018,"lang":"en","type":"article","venue":"Stroke","topic":"Acute Ischemic Stroke Management","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Medicine; Stroke (engine); Population; Triage; Emergency medicine","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":[0.006144821,0.001380169,0.001110383,0.001254751,0.0004331133,0.001882828,0.001881131,0.002221876,0.01018764],"category_scores_gemma":[0.02260231,0.0006876765,0.00305214,0.001053228,0.000857376,0.0007728128,0.001072425,0.002082026,0.0007537428],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002017515,"about_ca_system_score_gemma":0.001977169,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05767742,"about_ca_topic_score_gemma":0.01588143,"domain_scores_codex":[0.9983015,0.0009662999,0.00006586424,0.0003634963,0.00008410052,0.0002186782],"domain_scores_gemma":[0.9713475,0.0252457,0.001466216,0.0005659033,0.0008961934,0.0004785568],"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":[0.0005692138,0.0001453362,0.02832175,0.0001167976,0.0002419674,0.0001631224,0.00007912124,0.9614416,0.0001506934,0.002241181,0.001378659,0.005150423],"study_design_scores_gemma":[0.00008376552,0.0001747104,0.004303471,0.00003148405,0.0001040855,0.0000514542,0.00003754262,0.9925874,0.0001276189,0.002103517,0.0003795994,0.00001531515],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9246477,0.001016591,0.05418454,0.002452065,0.0001963229,0.0003328813,0.0119474,0.0005001816,0.004722273],"genre_scores_gemma":[0.989987,0.0001939535,0.005011289,0.0001147115,0.00003856382,0.0002275132,0.002172241,0.00003652758,0.002218213],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05767742,"threshold_uncertainty_score":0.1146834,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03125981036316672,"score_gpt":0.3228108122170318,"score_spread":0.2915510018538651,"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."}}