{"id":"W1591925817","doi":"10.1002/glia.22722","title":"White matter injury: Ischemic and nonischemic","year":2014,"lang":"en","type":"review","venue":"Glia","topic":"Neuroinflammation and Neurodegeneration Mechanisms","field":"Neuroscience","cited_by":104,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"Canadian Institutes of Health Research; Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas; Alberta Heritage Foundation for Medical Research; Canada Research Chairs; Biotechnology and Biological Sciences Research Council; Multiple Sclerosis Society of Canada","keywords":"Excitotoxicity; White matter; Grey matter; Neuroscience; Ischemia; Biology; Glutamate receptor; Oligodendrocyte; Microglia; Pathology; Brain ischemia; Stroke (engine); Receptor; Central nervous system; Medicine; Inflammation; Myelin; Immunology; Internal medicine; Genetics","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0001246821,0.0004001776,0.0007710912,0.0001607397,0.0001254751,0.0001598374,0.0003191409,0.0001977265,0.0006577621],"category_scores_gemma":[0.00009121578,0.0003413275,0.0001697907,0.0002168255,0.00006244981,0.0001342334,0.0001583293,0.0003931481,0.003957723],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001647229,"about_ca_system_score_gemma":0.00005375925,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":3.066392e-7,"about_ca_topic_score_gemma":2.038476e-7,"domain_scores_codex":[0.9980341,0.0002247967,0.0004842115,0.0007510752,0.0002329151,0.0002728905],"domain_scores_gemma":[0.9989278,0.00009646673,0.0003098176,0.0005168428,0.00001683045,0.0001322477],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001823251,0.00006464862,0.0000140127,0.0189048,0.00002031381,0.00006225516,0.0001005063,5.76101e-7,0.1154348,0.00542621,0.3105768,0.5493769],"study_design_scores_gemma":[0.00007833983,0.00002050802,4.085846e-7,0.0005458453,0.00006472843,0.0001219162,2.930615e-7,0.00001520084,0.02760978,0.00002985794,0.9711966,0.0003165282],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0007415705,0.9734562,0.0003589641,0.000471717,0.00188258,0.001555392,0.0001514215,0.0004683467,0.02091383],"genre_scores_gemma":[0.00005226811,0.9849257,0.0001416078,0.001868721,0.0002305513,0.00007206237,0.0000189964,0.00008517265,0.01260491],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.6606198,"threshold_uncertainty_score":0.9999039,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03889590390840909,"score_gpt":0.3092165824211935,"score_spread":0.2703206785127844,"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."}}