{"id":"W2437768564","doi":"10.1017/cjn.2016.68","title":"C.02: Whole genome expression profiling of blood-brain barrier endothelial cells after experimental subarachnoid hemorrhage","year":2016,"lang":"en","type":"article","venue":"Canadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques","topic":"Intracerebral and Subarachnoid Hemorrhage Research","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Systems, Applications & Products in Data Processing (Canada); Toronto Public Health; Calgary Laboratory Services","funders":"","keywords":"Gene expression profiling; PDGFRB; Subarachnoid hemorrhage; Gene expression; Molecular biology; Microarray; Microarray analysis techniques; Blood–brain barrier; Gene; Biology; Pathology; Medicine; Central nervous system; Neuroscience; Genetics; Internal medicine","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.0001955289,0.0002210892,0.0004802478,0.0005267672,0.0003524993,0.0003894756,0.0002037309,0.0003329396,0.00277014],"category_scores_gemma":[0.0001986119,0.0001142406,0.0003069955,0.0006585838,0.0002185269,0.0001115822,0.0001974529,0.0004436065,0.000572739],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002905933,"about_ca_system_score_gemma":0.0004144945,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002203968,"about_ca_topic_score_gemma":0.0034125,"domain_scores_codex":[0.999696,0.00002037351,0.00001285101,0.00009084149,0.0001045034,0.00007537533],"domain_scores_gemma":[0.9998567,0.000021711,0.00002993274,0.00001673623,0.00004166798,0.00003320034],"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":[0.0005483201,0.00005382682,0.002855462,0.00008133251,0.0000292248,0.00005353067,0.0000359081,0.00007085949,0.9913968,0.0000485793,0.000523622,0.0043024],"study_design_scores_gemma":[0.0000519867,0.0008975942,0.4304436,0.00002530707,0.0001931098,0.00078176,0.0001871113,0.001918486,0.556062,0.0001283783,0.00927735,0.00003342449],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9683566,0.001176487,0.007659468,0.0001916348,0.00007755803,0.0001114125,0.01964859,0.000353683,0.002424554],"genre_scores_gemma":[0.9270335,0.001716429,0.01483695,0.0005408217,0.0000499932,0.0006634499,0.04598447,0.0001849344,0.008989632],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00277014,"threshold_uncertainty_score":0.009266973,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02116232256061705,"score_gpt":0.2689714231703766,"score_spread":0.2478091006097595,"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."}}