{"id":"W2343848853","doi":"10.1161/circ.130.suppl_2.18789","title":"Abstract 18789: A Learning Collaborative Model to Improve Door to Needle Time for Stroke Thrombolysis in Chicago","year":2014,"lang":"en","type":"article","venue":"Circulation","topic":"Acute Ischemic Stroke Management","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Medicine; Thrombolysis; Stroke (engine); Triage; Tissue plasminogen activator; Baseline (sea); Quarter (Canadian coin); Emergency medicine; Internal medicine; Myocardial infarction","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":[0.00389138,0.0008878947,0.0005417567,0.001296695,0.00175196,0.002368084,0.00250259,0.001429563,0.01614299],"category_scores_gemma":[0.01024271,0.0003012903,0.0006098938,0.0007273518,0.0008256355,0.002410598,0.005094692,0.00133708,0.002884841],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002110616,"about_ca_system_score_gemma":0.007771233,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009409566,"about_ca_topic_score_gemma":0.01226189,"domain_scores_codex":[0.9978722,0.001035397,0.00007168892,0.0004769929,0.0002233722,0.0003202477],"domain_scores_gemma":[0.994666,0.001757387,0.0004040347,0.0002564561,0.0006861381,0.002230061],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.002984046,0.02047884,0.06560208,0.0005924574,0.0001853877,0.0007810768,0.006545625,0.1002863,0.003678527,0.01052279,0.06517225,0.7231707],"study_design_scores_gemma":[0.002886973,0.01030658,0.02228369,0.0004255022,0.0003953311,0.0002571734,0.008287646,0.8577743,0.002675573,0.02891803,0.06557831,0.00021089],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7212147,0.0007807487,0.1689633,0.01321658,0.0006501032,0.004120688,0.0006059851,0.007283176,0.0831647],"genre_scores_gemma":[0.8921956,0.0003486919,0.09323572,0.001247947,0.0001411737,0.001834061,0.0007130845,0.0001416238,0.01014212],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01614299,"threshold_uncertainty_score":0.05400372,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01212912486801917,"score_gpt":0.2713275933651667,"score_spread":0.2591984684971475,"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."}}