{"id":"W1995921508","doi":"10.1016/j.jprot.2013.10.018","title":"Serological autoantibody profiling of type 1 diabetes by protein arrays","year":2013,"lang":"en","type":"article","venue":"Journal of Proteomics","topic":"Diabetes and associated disorders","field":"Biochemistry, Genetics and Molecular Biology","cited_by":64,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Protein microarray; Autoantibody; Type 1 diabetes; Biomarker; Serology; DNA microarray; Proteomics; Antigen; Biomarker discovery; Proteome; Antibody; Biology; Computational biology; Immunology; Medicine; Bioinformatics; Diabetes mellitus; Gene; Genetics; Endocrinology; Gene expression","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":[0.0003297183,0.0003457372,0.0002603135,0.0008132972,0.0002314508,0.0005093276,0.0002080689,0.0003188025,0.000697682],"category_scores_gemma":[0.0005880659,0.0001780079,0.0001976096,0.0005356608,0.0001164714,0.000205715,0.0002414183,0.0004668038,0.0003985965],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001292476,"about_ca_system_score_gemma":0.0001013052,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002557147,"about_ca_topic_score_gemma":0.0004869156,"domain_scores_codex":[0.9996531,0.00008337403,0.00002924176,0.00009544214,0.00009040495,0.0000484694],"domain_scores_gemma":[0.9997347,0.00008875682,0.00005939612,0.00002371774,0.00006329249,0.00003020185],"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":[0.0002236857,0.00004627631,0.0133749,0.00004693428,0.00003632057,0.00004840958,0.000029518,0.0001422795,0.9774755,0.00006258551,0.0001733496,0.008340137],"study_design_scores_gemma":[0.00002992047,0.0005274446,0.2335586,0.0000249637,0.000184013,0.001061145,0.0001490342,0.009240625,0.7514536,0.0005792573,0.00315977,0.00003163343],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9803427,0.001844265,0.01324659,0.0001932893,0.00005602036,0.00004753257,0.001533541,0.000173754,0.002562443],"genre_scores_gemma":[0.9820409,0.001054149,0.01319453,0.0003228259,0.00005323988,0.00008885936,0.00152114,0.00002683398,0.001697574],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0008132972,"threshold_uncertainty_score":0.002333939,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005702543589153956,"score_gpt":0.2189775444288488,"score_spread":0.2132750008396949,"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."}}