{"id":"W2154722286","doi":"10.1093/bioinformatics/btr556","title":"miREnvironment Database: providing a bridge for microRNAs, environmental factors and phenotypes","year":2011,"lang":"en","type":"article","venue":"Bioinformatics","topic":"MicroRNA in disease regulation","field":"Biochemistry, Genetics and Molecular Biology","cited_by":74,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Research Council Canada","keywords":"Phenotype; microRNA; Biology; Computational biology; Organism; Database; Bioinformatics; Genetics; Computer science; Gene","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00006885896,0.0001372726,0.00008533301,0.00002494548,0.00007556499,0.00001537258,0.00008875142,0.00006955758,0.00001942556],"category_scores_gemma":[0.00001719028,0.000122721,0.00004614924,0.00001340771,0.00007202919,0.0000139328,0.0001085808,0.00002526773,0.000006397529],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002049024,"about_ca_system_score_gemma":0.00001624661,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003815705,"about_ca_topic_score_gemma":0.000002177177,"domain_scores_codex":[0.999422,0.000008157119,0.0001941482,0.0001388425,0.00006988492,0.0001669875],"domain_scores_gemma":[0.9995918,0.000006164508,0.00009952387,0.0002203145,0.000004773231,0.00007741817],"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":[0.0001138344,0.0001330256,0.02160892,0.0002121776,0.000102415,4.892485e-7,0.001092115,0.000001786829,0.969245,0.0001024199,0.002160276,0.00522752],"study_design_scores_gemma":[0.0009940504,0.0002708452,0.1169802,0.00002828044,0.00008979991,0.00001356147,0.0004375555,0.001507297,0.8381187,0.00004053752,0.04104825,0.0004709584],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9875528,0.0004244755,0.011053,0.000006847357,0.00005301282,0.0004261307,0.0003561781,0.000009946437,0.0001176652],"genre_scores_gemma":[0.9787949,0.0001152255,0.01966462,0.00006244779,0.00004521518,0.00002263941,0.001215614,0.00001783717,0.0000615582],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1311263,"threshold_uncertainty_score":0.5004416,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02372183527517547,"score_gpt":0.2219915743072171,"score_spread":0.1982697390320416,"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."}}