{"id":"W4389441444","doi":"10.3390/biology12121500","title":"Proteome Profiling of Brain Vessels in a Mouse Model of Cerebrovascular Pathology","year":2023,"lang":"en","type":"article","venue":"Biology","topic":"S100 Proteins and Annexins","field":"Biochemistry, Genetics and Molecular Biology","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital; Université de Montréal; Institut Universitaire de Gériatrie de Montréal; National Research Council Canada","funders":"National Research Council Canada; Canadian Institutes of Health Research","keywords":"Proteome; Biology; Proteomics; Biomarker; Dementia; Inflammation; Pathology; Genetically modified mouse; Vascular dementia; Blood proteins; Bioinformatics; Transgene; Disease; Endocrinology; Immunology; Medicine; Biochemistry; Gene","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":[0.0002622736,0.0005346689,0.0003813088,0.001064729,0.0002602169,0.0004187091,0.0002264743,0.0004925033,0.0008246193],"category_scores_gemma":[0.0001615891,0.0002441823,0.0003458111,0.0003861648,0.0003075929,0.0002879177,0.0002445947,0.0009115717,0.0003500518],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000236451,"about_ca_system_score_gemma":0.0001416509,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004088856,"about_ca_topic_score_gemma":0.0005847048,"domain_scores_codex":[0.9997794,0.00002022153,0.00001808631,0.00008417283,0.00005988749,0.00003825945],"domain_scores_gemma":[0.9997284,0.00002737978,0.0001011458,0.00002185052,0.00004981962,0.00007135311],"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":[0.0001577755,0.00002618928,0.0003186506,0.00002453535,0.00001419974,0.00005596181,0.00001723087,0.00002289011,0.9986116,0.00005487365,0.00005663967,0.0006395777],"study_design_scores_gemma":[0.00004200089,0.0007340537,0.0374638,0.00002715278,0.0001513694,0.001202851,0.00009738306,0.002272517,0.9533283,0.0003181259,0.004334787,0.00002762093],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9812837,0.001893471,0.01167628,0.0002041984,0.0001230458,0.0000748997,0.00331166,0.0003193102,0.001113412],"genre_scores_gemma":[0.9636475,0.004295725,0.01872834,0.0002947754,0.00007514934,0.000358076,0.006120994,0.0002410061,0.006238444],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001064729,"threshold_uncertainty_score":0.002758682,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02160754614487895,"score_gpt":0.2708129888349642,"score_spread":0.2492054426900852,"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."}}