{"id":"W2080764623","doi":"10.1038/sj.jcbfm.9591524.0250","title":"Characterization of vascular protein expression patterns in cerebral ischemia/reperfusion using laser capture microdissection and ICAT-LC-MS/MS","year":2005,"lang":"en","type":"article","venue":"Journal of Cerebral Blood Flow & Metabolism","topic":"Molecular Biology Techniques and Applications","field":"Biochemistry, Genetics and Molecular Biology","cited_by":5,"is_retracted":false,"has_abstract":false,"ca_institutions":"Institute for Biological Sciences","funders":"","keywords":"Laser capture microdissection; Microdissection; Ischemia; Brain ischemia; Protein expression; Medicine; Neuroscience; Gene expression; Cardiology; Chemistry; Psychology; Gene; Biochemistry","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":[0.0002879021,0.0003779118,0.0004612505,0.0009759506,0.0005866241,0.0005300278,0.0003596689,0.0003634249,0.001479874],"category_scores_gemma":[0.00043112,0.0002071678,0.0003610343,0.0006621113,0.0003340116,0.0005151557,0.0001670005,0.0006587426,0.0006968885],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003445144,"about_ca_system_score_gemma":0.0003844025,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001599316,"about_ca_topic_score_gemma":0.003134469,"domain_scores_codex":[0.9998459,0.00001013863,0.000009979086,0.00004779156,0.00004026365,0.00004584433],"domain_scores_gemma":[0.9997489,0.00005999548,0.00004923289,0.00002361258,0.00008221552,0.00003603048],"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":[0.0001348589,0.00001600548,0.0003050813,0.00003015708,0.000006920086,0.00003493858,0.00002149722,0.00001558151,0.9975294,0.00004870953,0.0000690311,0.001787857],"study_design_scores_gemma":[0.00003309797,0.0003142816,0.05011074,0.0000103006,0.0001189745,0.0007732259,0.00008735128,0.001046362,0.9443918,0.0002075845,0.002887538,0.00001864412],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9419318,0.005038715,0.04254783,0.0005291061,0.0001514747,0.0002062245,0.004626617,0.0005423498,0.004425857],"genre_scores_gemma":[0.9154275,0.006449527,0.05525957,0.000680041,0.0002242304,0.001139241,0.006448239,0.0002650595,0.01410659],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001599316,"threshold_uncertainty_score":0.004950643,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005115449835987851,"score_gpt":0.2242418675328861,"score_spread":0.2191264176968982,"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."}}