{"id":"W2990897838","doi":"10.1136/neurintsurg-2019-015308","title":"Patients with low Alberta Stroke Program Early CT Score (ASPECTS) but good collaterals benefit from endovascular recanalization","year":2019,"lang":"en","type":"article","venue":"Journal of NeuroInterventional Surgery","topic":"Acute Ischemic Stroke Management","field":"Medicine","cited_by":87,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Medicine; Modified Rankin Scale; Collateral circulation; Occlusion; Stroke (engine); Angiography; Radiology; Target lesion; Lesion; Clinical endpoint; Logistic regression; Endovascular treatment; Edema; Surgery; Internal medicine; Ischemic stroke; Aneurysm; Ischemia; Randomized controlled trial; Percutaneous coronary intervention","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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0002764303,0.0002493077,0.0006576052,0.000350227,0.00003900153,0.00007722832,0.0001594154,0.0000431816,0.001171793],"category_scores_gemma":[0.0001404525,0.0001970269,0.0008569764,0.0002369561,0.00003650627,0.000340365,0.00007259892,0.0002747755,0.00005799422],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001484033,"about_ca_system_score_gemma":0.0001058333,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002196855,"about_ca_topic_score_gemma":0.00002419909,"domain_scores_codex":[0.9972069,0.00007635396,0.0009634373,0.0003142735,0.0011496,0.0002894899],"domain_scores_gemma":[0.9977582,0.0002701594,0.0009368646,0.000316509,0.0005195042,0.0001987244],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0008445016,0.001048826,0.9887049,0.0001373807,0.001218433,0.0004208857,0.00001491592,0.0000688462,0.0009933874,0.00003288786,0.004178779,0.002336239],"study_design_scores_gemma":[0.003028775,0.001149462,0.9839818,0.001668965,0.0003999447,0.0002360405,0.00001335371,0.00007103558,0.00120822,0.00002946695,0.008020801,0.0001921514],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9968278,0.0001274454,0.00009273679,0.0003901731,0.000657186,0.0006349584,0.00005487495,0.00002172392,0.001193114],"genre_scores_gemma":[0.9943966,0.00002409827,0.0004038983,0.000218368,0.0002422053,0.000008634203,0.0001549351,0.00005190516,0.004499365],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004723135,"threshold_uncertainty_score":0.9997413,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01228391244410507,"score_gpt":0.2305600557941861,"score_spread":0.218276143350081,"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."}}