{"id":"W4238074889","doi":"10.3410/f.722007580.793501829","title":"Faculty Opinions recommendation of Validity of acute stroke lesion volume estimation by diffusion-weighted imaging-Alberta Stroke Program Early Computed Tomographic Score depends on lesion location in 496 patients with middle cerebral artery stroke.","year":2014,"lang":"en","type":"dataset","venue":"Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature","topic":"Acute Ischemic Stroke Management","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Computed tomographic; Stroke (engine); Medicine; Lesion; Acute stroke; Volume (thermodynamics); Radiology; Nuclear medicine; Computed tomography; Internal medicine; Surgery; Engineering","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":[0.003533622,0.001096505,0.001385896,0.003227184,0.0005598878,0.002081816,0.00268259,0.001695456,0.04891531],"category_scores_gemma":[0.04725376,0.0006356012,0.001872487,0.004281834,0.00031483,0.001323441,0.001498831,0.001219083,0.02319145],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001596442,"about_ca_system_score_gemma":0.004427546,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03128802,"about_ca_topic_score_gemma":0.05610665,"domain_scores_codex":[0.997062,0.0005596299,0.0006828246,0.0007707555,0.000701703,0.0002229443],"domain_scores_gemma":[0.9820894,0.00538297,0.003522885,0.002526252,0.005362327,0.001116113],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.0003593226,0.00004566611,0.02895086,0.0009873023,0.0004278341,0.00002384713,0.00002012954,0.000205409,0.00007744714,0.0002487033,0.962777,0.005876495],"study_design_scores_gemma":[0.006529883,0.0001188489,0.2645261,0.003285817,0.001597459,0.0003589748,0.0002194525,0.003221861,0.001205005,0.002220462,0.7165204,0.0001956415],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.001185083,0.00008756905,0.00008594945,0.000368801,0.00004139658,0.00004668127,0.9971655,0.00008984288,0.0009291656],"genre_scores_gemma":[0.005512312,0.0001224998,0.0005694634,0.0003363219,0.00005314874,0.0003310374,0.9919083,0.00006484682,0.001102102],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.04891531,"threshold_uncertainty_score":0.163638,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02341511867530302,"score_gpt":0.3054943290595319,"score_spread":0.2820792103842289,"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."}}