{"id":"W2786238001","doi":"10.1136/bmj.j5745","title":"Development and validation of outcome prediction models for aneurysmal subarachnoid haemorrhage: the SAHIT multinational cohort study","year":2018,"lang":"en","type":"article","venue":"BMJ","topic":"Intracranial Aneurysms: Treatment and Complications","field":"Medicine","cited_by":282,"is_retracted":false,"has_abstract":true,"ca_institutions":"St. Michael's Hospital; University of Toronto","funders":"Canadian Institutes of Health Research; King's College London; Universitätsspital Zürich; Montreal Neurological Institute and Hospital; University of Toronto; Inselspital, Universitätsspital Bern; McGill University","keywords":"Medicine; Confidence interval; Observational study; Glasgow Outcome Scale; Cohort; Subarachnoid hemorrhage; Logistic regression; Clinical trial; Receiver operating characteristic; Prospective cohort study; Neuroimaging; Cohort study; Internal medicine; Glasgow Coma Scale; Surgery","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003277418,0.00008253968,0.0001284821,0.00004748533,0.0002039984,0.00001112439,0.00004862751,0.00003313795,0.00001818397],"category_scores_gemma":[0.00005428438,0.000056937,0.00002803615,0.00007883796,0.00005694293,0.00006736707,0.00002130025,0.00004343988,0.000006136778],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003288695,"about_ca_system_score_gemma":0.00004089832,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001540621,"about_ca_topic_score_gemma":0.00001400854,"domain_scores_codex":[0.9991961,0.00002093444,0.0003130125,0.0001666449,0.0002114338,0.00009190549],"domain_scores_gemma":[0.9993938,0.00005082299,0.00009654809,0.0001622188,0.0002677935,0.00002888031],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002678823,0.0007802742,0.988144,0.00006379523,0.00007320892,0.000003168138,0.0017333,0.00004238325,0.001000762,0.002077792,0.000256434,0.005557004],"study_design_scores_gemma":[0.001331693,0.0004240617,0.9734289,0.000003924325,0.0002330321,0.00006325812,0.0002494729,0.02024482,0.003535992,0.0002587698,0.0001603326,0.00006573227],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.990355,0.000007862189,0.005020659,0.001196402,0.00008452961,0.002514023,0.00002145827,0.00003365912,0.0007664749],"genre_scores_gemma":[0.9916192,2.346088e-7,0.006731208,0.00006551446,0.000193916,0.0005114358,0.00009251399,0.000008903285,0.0007771127],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02020244,"threshold_uncertainty_score":0.2321824,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04994315596447174,"score_gpt":0.3208879015690843,"score_spread":0.2709447456046125,"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."}}