{"id":"W4224251080","doi":"10.1101/2022.04.05.487234","title":"Extracellular Vesicle Antibody Microarray for Multiplexed Inner and Outer Protein Analysis","year":2022,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Extracellular vesicles in disease","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; McGill Genome Centre","funders":"Fonds de recherche du Québec – Nature et technologies; Genome Canada; Natural Sciences and Engineering Research Council of Canada; McGill University","keywords":"Cell biology; Biology; Extracellular vesicle; Microvesicles; Proteomics; Cold-shock domain; Molecular biology; Chemistry; Biochemistry; Gene; RNA; microRNA","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":[0.0004366302,0.0005931344,0.0006108569,0.0008419971,0.0002363449,0.0005015076,0.0004526954,0.0007164191,0.001923788],"category_scores_gemma":[0.0003859666,0.0003641029,0.00033007,0.0004738636,0.0001472568,0.0003002434,0.0004380587,0.0005295618,0.001196992],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003928544,"about_ca_system_score_gemma":0.0001955268,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003812597,"about_ca_topic_score_gemma":0.000816803,"domain_scores_codex":[0.999272,0.0001017864,0.00004208197,0.0002625289,0.0002439098,0.0000776188],"domain_scores_gemma":[0.9998254,0.00005407218,0.00002263024,0.00001990267,0.00005819156,0.00001977179],"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":[0.00003995584,0.00002663067,0.000241243,0.00003963605,0.0000090677,0.00001658799,0.000008996826,0.0002195439,0.9949113,0.0001505611,0.0001779035,0.00415871],"study_design_scores_gemma":[0.000006949999,0.00008928431,0.002253416,0.000006634038,0.00001661266,0.00006838051,0.00001131378,0.01257315,0.9814433,0.0001470773,0.003370434,0.00001342345],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.5239384,0.002232107,0.4574719,0.00040658,0.0002658362,0.0004616273,0.005496091,0.003497612,0.006229913],"genre_scores_gemma":[0.4430115,0.001523586,0.5387928,0.0003589092,0.0000986155,0.001297963,0.004554973,0.000229734,0.01013197],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.001923788,"threshold_uncertainty_score":0.006435752,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009500530198044851,"score_gpt":0.2398441184106649,"score_spread":0.2303435882126201,"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."}}