{"id":"W4387361906","doi":"10.1210/jendso/bvad114.707","title":"THU271 Identification Of Candidate Biomarkers For Type 1 Diabetes Mellitus By Bioinformatics Analysis Of Pooled Microarray Gene Expression Datasets In Gene Expression Omnibus","year":2023,"lang":"en","type":"article","venue":"Journal of the Endocrine Society","topic":"Pancreatic function and diabetes","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"York University","keywords":"KEGG; Biology; Gene; Microarray analysis techniques; Candidate gene; Gene expression profiling; Gene expression; Transcriptome; Microarray; Computational biology; Genetics; Bioinformatics","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001775411,0.0006742465,0.001492181,0.003357834,0.0005879939,0.001241807,0.0005446704,0.0003174849,0.004671626],"category_scores_gemma":[0.001999278,0.000296559,0.001428601,0.003651085,0.0001915527,0.0003338973,0.0006685424,0.0006927734,0.001002882],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005193687,"about_ca_system_score_gemma":0.001187843,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001550986,"about_ca_topic_score_gemma":0.00338511,"domain_scores_codex":[0.9989415,0.0002694404,0.00009533255,0.0002928513,0.0002633537,0.0001374792],"domain_scores_gemma":[0.9992888,0.0002966167,0.0001479342,0.0000505418,0.000148829,0.00006733225],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.008408902,0.001019075,0.4356007,0.005164321,0.004888301,0.001711191,0.0006245641,0.01528371,0.2831728,0.00269939,0.03690763,0.2045194],"study_design_scores_gemma":[0.0006135366,0.001469964,0.7202126,0.0003225858,0.002434474,0.001835264,0.0008593873,0.1782666,0.04791616,0.005180264,0.04068473,0.0002044434],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7469296,0.006823443,0.07831299,0.001350605,0.0003113751,0.0008432772,0.15602,0.003806824,0.005601819],"genre_scores_gemma":[0.7617542,0.001883348,0.1288597,0.0005936132,0.0001015129,0.002251777,0.1019992,0.0004238601,0.002132741],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004671626,"threshold_uncertainty_score":0.01562816,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01675141781544398,"score_gpt":0.2927322762785651,"score_spread":0.2759808584631211,"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."}}