{"id":"W4311404624","doi":"10.1021/acssensors.2c01750","title":"Extracellular Vesicle Antibody Microarray for Multiplexed Inner and Outer Protein Analysis","year":2022,"lang":"en","type":"article","venue":"ACS Sensors","topic":"Extracellular vesicles in disease","field":"Biochemistry, Genetics and Molecular Biology","cited_by":27,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; McGill Genome Centre","funders":"Fonds de recherche du Québec – Nature et technologies; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs; Génome Québec; Genome Canada","keywords":"Cell biology; Biology; Proteomics; Microvesicles; Protein microarray; Extracellular vesicle; Computational biology; Molecular biology; Chemistry; Microarray; Gene expression; Biochemistry; Gene; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000294766,0.000188042,0.0001980947,0.0001060679,0.000261404,0.00003494213,0.0002150278,0.00008344639,0.00005694024],"category_scores_gemma":[0.00008965425,0.0002023003,0.0001851709,0.0002386526,0.000093852,0.000005430528,0.0002291304,0.0001083838,0.000004247484],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000214349,"about_ca_system_score_gemma":0.00003159185,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000016088,"about_ca_topic_score_gemma":0.000006770551,"domain_scores_codex":[0.9985892,0.0001350586,0.0002460299,0.0005547579,0.0001584925,0.0003164753],"domain_scores_gemma":[0.9991818,0.00001939302,0.0001089715,0.0005146156,0.00006036571,0.0001148564],"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":[0.0001670725,0.0001217197,0.00480951,0.00002185381,0.0003205019,0.00002128632,0.0000938075,0.0007221944,0.9927203,0.00008652639,0.0006440985,0.0002711448],"study_design_scores_gemma":[0.001287706,0.0002516605,0.002336957,0.000003202999,0.0003550647,0.00001717623,0.0003865948,0.001552504,0.9077208,0.00008305559,0.08555144,0.0004538484],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9952778,0.002117935,0.001442394,0.0002554323,0.00006024484,0.0006148641,0.0001479302,0.00002321711,0.00006015792],"genre_scores_gemma":[0.989158,0.00001315255,0.003852162,0.0001288047,0.000102954,0.0001452968,0.0005943401,0.00004480756,0.005960421],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08499949,"threshold_uncertainty_score":0.8249567,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008645372098938195,"score_gpt":0.2536775428907669,"score_spread":0.2450321707918287,"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."}}