{"id":"W1994504524","doi":"10.1161/01.str.0000150492.12838.66","title":"Optimizing Discharge Planning","year":2004,"lang":"en","type":"article","venue":"Stroke","topic":"Acute Ischemic Stroke Management","field":"Medicine","cited_by":34,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ontario Stroke Network","funders":"Canadian Institutes of Health Research; Heart and Stroke Foundation of Canada","keywords":"Medicine; Stroke (engine); Modified Rankin Scale; Logistic regression; Odds ratio; Multivariate analysis; Thrombolysis; Tissue plasminogen activator; Infarction; Internal medicine; Fibrinolytic agent; Acute stroke; Emergency medicine; Surgery; Ischemic stroke; Myocardial infarction; Ischemia","routes":{"ca_aff":true,"ca_fund":true,"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":[0.001793827,0.0007463671,0.0004071791,0.001352087,0.001283754,0.00374073,0.001328874,0.001018238,0.03952205],"category_scores_gemma":[0.01146735,0.0002007984,0.0004917544,0.001139765,0.0004637093,0.001505604,0.002567148,0.001628459,0.008173281],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002292452,"about_ca_system_score_gemma":0.01241153,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006584798,"about_ca_topic_score_gemma":0.01032529,"domain_scores_codex":[0.9981934,0.0007713932,0.0001360634,0.0002082148,0.0003486907,0.0003423085],"domain_scores_gemma":[0.9969163,0.0005667041,0.0003200782,0.0002047471,0.0009723114,0.001019837],"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":[0.0002023051,0.0004558081,0.02051431,0.0003717768,0.0000437266,0.000760214,0.0007663883,0.01834556,0.000375569,0.02029465,0.2700813,0.6677884],"study_design_scores_gemma":[0.0005361247,0.0007824283,0.04914131,0.003521843,0.0001712829,0.003002795,0.01494583,0.08989254,0.002112372,0.2211735,0.6145321,0.000187917],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.1061784,0.009003401,0.3602655,0.1131141,0.003435411,0.003531737,0.005836043,0.006558546,0.3920768],"genre_scores_gemma":[0.6570079,0.009870247,0.2619636,0.006285244,0.0009409157,0.001690688,0.007161779,0.0009416952,0.05413784],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.03952205,"threshold_uncertainty_score":0.1322144,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01961359829366847,"score_gpt":0.2795552770053659,"score_spread":0.2599416787116974,"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."}}