{"id":"W2548607613","doi":"10.1007/s10334-016-0597-5","title":"Magnetic resonance imaging detection of multiple ischemic injury produced in an adult rat model of minor stroke followed by mild transient cerebral ischemia","year":2016,"lang":"en","type":"article","venue":"Magnetic Resonance Materials in Physics Biology and Medicine","topic":"Acute Ischemic Stroke Management","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"Canadian Institutes of Health Research; University of Calgary","keywords":"Ischemia; Medicine; Magnetic resonance imaging; Stroke (engine); Lesion; Exacerbation; Middle cerebral artery; Necrosis; Histology; Brain damage; Infarction; Central nervous system disease; Cardiology; Pathology; Internal medicine; Anesthesia; Radiology; Myocardial infarction","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003737611,0.001118921,0.0007507506,0.0008202603,0.0002656651,0.0002578225,0.0003703861,0.0006220316,0.001883206],"category_scores_gemma":[0.0001632177,0.0004614114,0.0004413488,0.0002992974,0.0005472977,0.0003840127,0.0002764522,0.001438538,0.0004516097],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003438791,"about_ca_system_score_gemma":0.0004607952,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002069329,"about_ca_topic_score_gemma":0.004382971,"domain_scores_codex":[0.9998549,0.00001164875,0.00001287853,0.00003307583,0.00002760531,0.00005983589],"domain_scores_gemma":[0.9997482,0.00001199808,0.00008470085,0.00002530265,0.00004208725,0.00008772949],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001953568,0.0004737013,0.0004962433,0.00008234804,0.00002340917,0.0003745088,0.0000552112,0.00008188264,0.9942976,0.00008331484,0.0001086483,0.001969636],"study_design_scores_gemma":[0.0003189256,0.02552981,0.02260957,0.00004150442,0.0002290201,0.001851735,0.0002257042,0.001337842,0.9461111,0.000159503,0.001556339,0.00002888129],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9948208,0.0008129488,0.002622383,0.0001141407,0.00008891461,0.000125074,0.0003195337,0.0001506514,0.0009455848],"genre_scores_gemma":[0.9852735,0.00180683,0.004858523,0.0001240119,0.00004324329,0.0003411501,0.0006555507,0.00002900762,0.006868137],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002069329,"threshold_uncertainty_score":0.006299973,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009785185877269691,"score_gpt":0.2530786536948594,"score_spread":0.2432934678175897,"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."}}