{"id":"W2723050023","doi":"10.1007/s12975-017-0547-1","title":"MicroRNA Changes in Preconditioning-Induced Neuroprotection","year":2017,"lang":"en","type":"review","venue":"Translational Stroke Research","topic":"MicroRNA in disease regulation","field":"Biochemistry, Genetics and Molecular Biology","cited_by":27,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"National Institute of Neurological Disorders and Stroke; National Institutes of Health","keywords":"Neuroprotection; Ischemic preconditioning; microRNA; Medicine; Ischemia; Neuroscience; Mechanism (biology); Neurology; Stroke (engine); Pharmacology; Anesthesia; Biology; Cardiology; Gene","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000644342,0.001086811,0.001533797,0.001165469,0.0002475286,0.001080362,0.0007108041,0.001174175,0.001999159],"category_scores_gemma":[0.0006483847,0.0003034889,0.0003301958,0.001570103,0.0006882302,0.00120142,0.0009214832,0.002044453,0.001322265],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005581928,"about_ca_system_score_gemma":0.001093176,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005061149,"about_ca_topic_score_gemma":0.001351017,"domain_scores_codex":[0.9998549,0.00002053921,0.00002945893,0.00003082489,0.00004602927,0.00001819655],"domain_scores_gemma":[0.9997843,0.00009524034,0.00003612338,0.000008049116,0.00004878054,0.0000275491],"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":[0.0001663966,0.00006210413,0.0002049875,0.01072833,0.00008615367,0.0002397146,0.00005366116,0.0004028442,0.005525718,0.005352557,0.02581048,0.9513671],"study_design_scores_gemma":[0.00003633472,0.000112225,0.001283371,0.003057653,0.0002228235,0.001226004,0.0000898244,0.0002397831,0.003229421,0.005408657,0.9850522,0.00004172914],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0001362964,0.9983128,0.0002421934,0.0002648538,0.0003517598,0.000003258139,0.00001823024,0.000008717487,0.0006618393],"genre_scores_gemma":[0.001038381,0.9976562,0.0002494001,0.0002302089,0.0003339574,0.000008197189,0.00002986518,0.000002603603,0.0004510494],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.001999159,"threshold_uncertainty_score":0.00668788,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2248150357876997,"score_gpt":0.451257795067223,"score_spread":0.2264427592795233,"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."}}