{"id":"W4387479018","doi":"10.1093/database/baad063","title":"ESOMIR: a curated database of biomarker genes and miRNAs associated with esophageal cancer","year":2023,"lang":"en","type":"article","venue":"Database","topic":"MicroRNA in disease regulation","field":"Biochemistry, Genetics and Molecular Biology","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"Shanghai Jiao Tong University; Science and Technology Commission of Shanghai Municipality; King Saud University; National Natural Science Foundation of China; National Science Foundation","keywords":"microRNA; Database; Gene; Computational biology; Biomarker; Bioinformatics; Biology; Computer science; Genetics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001618232,0.000131939,0.0001240821,0.00006990707,0.00004928905,0.00001302734,0.00009906504,0.00006278377,0.00004777598],"category_scores_gemma":[0.00009648337,0.0001157613,0.00002688623,0.0002828528,0.0001057273,0.00001226559,0.0001576215,0.00003693904,0.00000591579],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001101902,"about_ca_system_score_gemma":0.0000935382,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001640726,"about_ca_topic_score_gemma":0.0002844332,"domain_scores_codex":[0.9991503,0.00006061647,0.0001572107,0.00031559,0.0001290686,0.0001872603],"domain_scores_gemma":[0.9993179,0.00001849411,0.0001067556,0.0003727382,0.00009446224,0.00008965532],"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":[0.0001705914,0.00005404557,0.01571206,0.00006118438,0.0001457447,0.00002697754,0.00001202999,0.00001860319,0.9735283,0.00001682286,0.009469345,0.0007843354],"study_design_scores_gemma":[0.0025093,0.0001114338,0.1467094,0.0002242223,0.0001778231,0.00001322873,0.00004443054,0.002406565,0.8387257,0.000007357799,0.008658612,0.0004120074],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9912505,0.002169358,0.0001280539,0.00005271736,0.00004868482,0.0001862676,0.006113337,0.00002851332,0.00002262552],"genre_scores_gemma":[0.9784879,0.0006079196,0.0002297726,0.00005097438,0.00004459734,0.00003791273,0.02029317,0.00002745545,0.0002203125],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1348026,"threshold_uncertainty_score":0.4720609,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02180211341234496,"score_gpt":0.2858928727710026,"score_spread":0.2640907593586576,"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."}}