{"id":"W3007782052","doi":"10.1186/s12920-020-0660-y","title":"Discovery of inflammatory bowel disease-associated miRNAs using a novel bipartite clustering approach","year":2020,"lang":"en","type":"article","venue":"BMC Medical Genomics","topic":"MicroRNA in disease regulation","field":"Biochemistry, Genetics and Molecular Biology","cited_by":22,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"Mitacs; Nara Institute of Science and Technology; Research Manitoba; Health Sciences Centre Foundation","keywords":"microRNA; Inflammatory bowel disease; Disease; Computational biology; DNA microarray; Ranking (information retrieval); Biology; Cluster analysis; Bioinformatics; Gene; Medicine; Genetics; Computer science; Gene expression; Machine learning","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":[0.0001897514,0.0001435221,0.0001651561,0.00002396933,0.00003965482,0.00001938746,0.0002288511,0.0001663286,0.00001197692],"category_scores_gemma":[0.0006207653,0.0001472805,0.0001365367,0.00007348666,0.0001175669,0.000007542236,0.0002691459,0.0000816753,0.000002341122],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004344452,"about_ca_system_score_gemma":0.0006490299,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005186596,"about_ca_topic_score_gemma":0.00001316273,"domain_scores_codex":[0.9987897,0.00005982978,0.0003570523,0.0003144777,0.0002692484,0.0002096905],"domain_scores_gemma":[0.9992029,0.00001903684,0.0001743047,0.0002327141,0.00004510443,0.0003259097],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002947114,0.0001493793,0.0184415,0.0003525683,0.00009590694,0.000003210679,0.00008554625,0.009174415,0.9711478,0.00004212847,0.000129111,0.00008372919],"study_design_scores_gemma":[0.00382011,0.0001377698,0.07884935,0.0002263669,0.0002552239,0.00001529401,0.0001818479,0.8498597,0.06327309,0.00003568416,0.002475402,0.0008702179],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8416177,0.0004596441,0.1575274,0.00004222686,0.00006430161,0.0001674805,0.00006086678,0.00001208172,0.0000482242],"genre_scores_gemma":[0.9932478,0.00004909415,0.005814936,0.0002797269,0.0003101688,0.000007751869,0.0002333391,0.00003420263,0.00002294511],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9078747,"threshold_uncertainty_score":0.6005925,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02957278610675709,"score_gpt":0.2492202736543197,"score_spread":0.2196474875475626,"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."}}