{"id":"W2773088766","doi":"10.1212/wnl.0000000000004714","title":"Author response: Evaluation of hyperacute infarct volume using ASPECTS and brain CT perfusion core volume","year":2017,"lang":"en","type":"letter","venue":"Neurology","topic":"Acute Ischemic Stroke Management","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Medicine; Perfusion scanning; Brain size; Acute stroke; Stroke (engine); Volume (thermodynamics); Cardiology; Cerebral blood volume; Core (optical fiber); Stroke volume; Perfusion; Internal medicine; Nuclear medicine; Radiology; Magnetic resonance imaging; Computer science; Ejection fraction; 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":[0.001464734,0.0008591273,0.001511351,0.0009093506,0.001130552,0.00159708,0.001720651,0.01737345,0.01285423],"category_scores_gemma":[0.01791382,0.0003882803,0.0008402758,0.0005906589,0.001185885,0.002250656,0.0007165085,0.01616311,0.01005256],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002448336,"about_ca_system_score_gemma":0.001526333,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003178382,"about_ca_topic_score_gemma":0.003679528,"domain_scores_codex":[0.9987503,0.0004046663,0.0002106961,0.0002018913,0.0002580983,0.000174286],"domain_scores_gemma":[0.995778,0.00184352,0.0002631784,0.0001548516,0.001515005,0.0004454577],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002065945,0.0000686452,0.003323446,0.0001171627,0.00002478558,0.01323065,0.0001477026,0.0002030324,0.0002598945,0.001409506,0.9681331,0.01287538],"study_design_scores_gemma":[0.0007616965,0.00051153,0.009667064,0.001660089,0.0001325086,0.05868223,0.002457012,0.0048069,0.001468975,0.01746286,0.9020531,0.0003360366],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.001457879,0.0007627248,0.0003718149,0.9795305,0.01323611,0.0001019696,0.0002538497,0.0001628162,0.00412239],"genre_scores_gemma":[0.02403193,0.001449776,0.001255421,0.9312647,0.02982171,0.0002225802,0.0002319643,0.00007516307,0.01164677],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.01737345,"threshold_uncertainty_score":0.04300165,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06726390646281373,"score_gpt":0.3438693459637778,"score_spread":0.2766054395009641,"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."}}