{"id":"W4406993104","doi":"10.1161/str.56.suppl_1.ns1","title":"Abstract NS1: Identification of Subarachnoid Hemorrhage: The Impact of a Nurse Led Screening Tool Utilizing the Ottawa Rule","year":2025,"lang":"en","type":"article","venue":"Stroke","topic":"Acute Ischemic Stroke Management","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Medicine; Subarachnoid hemorrhage; Stroke (engine); Identification (biology); Intracerebral hemorrhage; Intensive care medicine; Internal medicine","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008093462,0.0005225799,0.0006164255,0.001265517,0.001136022,0.0026116,0.001468826,0.0005464694,0.007990179],"category_scores_gemma":[0.07157116,0.0002726855,0.001102348,0.000867249,0.0004089113,0.001512152,0.00196679,0.0009080354,0.001435425],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003997082,"about_ca_system_score_gemma":0.01451672,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.08072682,"about_ca_topic_score_gemma":0.08229887,"domain_scores_codex":[0.9885306,0.005399656,0.001697106,0.0007980273,0.003022822,0.0005518372],"domain_scores_gemma":[0.9539573,0.02213839,0.0061895,0.001364065,0.01171203,0.004638779],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001804664,0.001451889,0.7440877,0.001118593,0.0002861326,0.0003299578,0.001260906,0.002488034,0.0002024004,0.0004874364,0.02756438,0.2189178],"study_design_scores_gemma":[0.0007286738,0.006841021,0.8973957,0.003794235,0.00101621,0.001300465,0.009791384,0.04220227,0.002883041,0.002033505,0.0316394,0.0003741531],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9107013,0.001577754,0.005124683,0.01626314,0.0008295508,0.003079028,0.007336647,0.001023346,0.05406456],"genre_scores_gemma":[0.9757898,0.0007973362,0.01652138,0.001148812,0.00009989431,0.0005277399,0.002159686,0.00005302357,0.002902429],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08072682,"threshold_uncertainty_score":0.1605138,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01404066860833999,"score_gpt":0.3001478051578264,"score_spread":0.2861071365494864,"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."}}