{"id":"W4391438753","doi":"10.1161/str.55.suppl_1.wp64","title":"Abstract WP64: Assessment of a Smartphone App-Sensor to Assist Patients in Identification of Neurologic and Cardiac Emergencies: The Emergency Call for Heart Attack and Stroke (ECHAS) Study","year":2024,"lang":"en","type":"article","venue":"Stroke","topic":"Cardiovascular Health and Risk Factors","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Medicine; Triage; Emergency department; Hotline; Stroke (engine); Myocardial infarction; Emergency medicine; Acute stroke; Medical emergency; Emergency medical services; Internal medicine","routes":{"ca_aff":true,"ca_fund":false,"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":[0.004823288,0.001102615,0.0008831906,0.0008106577,0.001015051,0.001882432,0.0009568717,0.001583096,0.002127144],"category_scores_gemma":[0.01112867,0.0006589448,0.001530953,0.0007746078,0.0006887843,0.001413728,0.001233654,0.001507343,0.001381291],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009707032,"about_ca_system_score_gemma":0.001728288,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01992207,"about_ca_topic_score_gemma":0.01836842,"domain_scores_codex":[0.9983011,0.0006490065,0.0002178571,0.0002615006,0.0003998897,0.0001706678],"domain_scores_gemma":[0.9929708,0.001443026,0.001526739,0.0005447013,0.002351745,0.001162959],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.006514747,0.002894652,0.9798532,0.00021409,0.0009326058,0.0001814743,0.0005611451,0.000143477,0.0004351199,0.00003241728,0.002292901,0.005944123],"study_design_scores_gemma":[0.00217844,0.01368624,0.9775128,0.000136897,0.001190688,0.0004353768,0.001169651,0.0007874196,0.0003408855,0.00007986103,0.002416008,0.0000657956],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9958689,0.0002183293,0.0001229852,0.0001973278,0.00004732743,0.0006780974,0.001762419,0.00001113977,0.001093416],"genre_scores_gemma":[0.9928705,0.000281958,0.00045633,0.0004220997,0.0001066436,0.0009655575,0.003438235,0.00001365832,0.001444933],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01992207,"threshold_uncertainty_score":0.03961223,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02454786509486376,"score_gpt":0.3443165632599986,"score_spread":0.3197686981651349,"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."}}