{"id":"W2990310811","doi":"10.4103/ajns.ajns_242_19","title":"Value of brain computed tomographic angiography to predict post thrombectomy final infarct size and clinical outcome in acute ischemic stroke","year":2019,"lang":"en","type":"article","venue":"Asian Journal of Neurosurgery","topic":"Acute Ischemic Stroke Management","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Medicine; Computed tomographic angiography; Computed tomographic; Stroke (engine); Angiography; Radiology; Cardiology; Brain infarction; Acute stroke; Cerebral angiography; Internal medicine; Computed tomography; Ischemia","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":[0.0003622175,0.0002846197,0.0002003727,0.0005574038,0.0001825667,0.000378006,0.0002091529,0.000478076,0.001535396],"category_scores_gemma":[0.002612784,0.0001255455,0.0002255735,0.0002812076,0.0002905711,0.0002744591,0.0001826379,0.0003910795,0.0002259123],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001593776,"about_ca_system_score_gemma":0.0003473567,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001545026,"about_ca_topic_score_gemma":0.002574881,"domain_scores_codex":[0.9998218,0.00004994226,0.00002406185,0.0000260184,0.00004194041,0.00003615217],"domain_scores_gemma":[0.9988286,0.0003687867,0.0003466216,0.0000547917,0.0001364526,0.0002647105],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002122569,0.00002656022,0.9980487,0.00000621282,0.00002546651,0.0001038407,0.000009676992,0.00005295007,0.0001541287,0.000006703855,0.00005611984,0.001297382],"study_design_scores_gemma":[0.00001026733,0.0001516706,0.9984868,0.000006384937,0.00003308069,0.0006212768,0.00004164693,0.0004443052,0.00009227246,0.0000294191,0.00007956212,0.000003372718],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.998998,0.0003696234,0.0000798214,0.00006745273,0.00000944285,0.000007083222,0.0001115393,0.000003822562,0.0003532778],"genre_scores_gemma":[0.9995642,0.00008162079,0.0000604216,0.00001139281,0.00002302376,0.000004370544,0.000183031,8.018749e-7,0.00007111899],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001545026,"threshold_uncertainty_score":0.005136371,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01679640232946859,"score_gpt":0.293101006494786,"score_spread":0.2763046041653174,"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."}}