{"id":"W7161807111","doi":"10.82308/26902","title":"Effect of pre-existing conditions and non-neurological medical complications on mortality in aneurysmal subarachnoid hemorrhage patients undergoing angiography or neurosurgical clipping","year":2021,"lang":"en","type":"dissertation","venue":"","topic":"Intracranial Aneurysms: Treatment and Complications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Clipping (morphology); Subarachnoid hemorrhage; Aneurysm; Complication; Angiography; Mortality rate; Stroke (engine); Cerebral angiography","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":[0.00121369,0.0003396604,0.0003754208,0.001067085,0.0004976343,0.0009141794,0.0007425705,0.0004689743,0.002416892],"category_scores_gemma":[0.008014382,0.0002304863,0.001247352,0.001073132,0.0004362524,0.0004693224,0.000823221,0.001032579,0.0002051921],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001249482,"about_ca_system_score_gemma":0.001162767,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03934904,"about_ca_topic_score_gemma":0.05935962,"domain_scores_codex":[0.9988575,0.0002991648,0.0001342367,0.000209544,0.0003000969,0.000199541],"domain_scores_gemma":[0.9930483,0.001644068,0.003415948,0.0002945735,0.0004981463,0.001098841],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00007284575,0.00001328643,0.9994147,0.000006994042,0.00004092524,0.0000171877,0.00001361059,0.00001534632,0.000011333,0.00000400592,0.00003272923,0.0003571215],"study_design_scores_gemma":[0.000002839903,0.00005015935,0.9997323,0.000005450697,0.00002117671,0.00004220467,0.00003483554,0.00006791169,0.000008707034,0.000004647677,0.0000281122,0.000001619014],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9979483,0.0006984136,0.00004795318,0.0001309079,0.00001228661,0.00001396165,0.00059162,0.000004655471,0.0005519275],"genre_scores_gemma":[0.9991585,0.0002101034,0.0000557797,0.00002562319,0.00002379986,0.000007649806,0.0004351261,0.000001502997,0.00008195457],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03934904,"threshold_uncertainty_score":0.07824004,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01782952140301298,"score_gpt":0.3166696190902983,"score_spread":0.2988400976872853,"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."}}