{"id":"W4408163552","doi":"10.1093/nargab/lqaf011","title":"iModEst: disentangling -omic impacts on gene expression variation across genes and tissues","year":2025,"lang":"en","type":"article","venue":"NAR Genomics and Bioinformatics","topic":"Genomics and Chromatin Dynamics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Institute for Advanced Research; SickKids Foundation; Vector Institute; University of Toronto","funders":"","keywords":"Gene; Biology; Variation (astronomy); Genetics; Gene expression; Computational biology; Genetic variation; Evolutionary biology","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":[0.002179487,0.0009294575,0.00102641,0.001715928,0.0003924312,0.001497647,0.0007714171,0.0003757865,0.003047712],"category_scores_gemma":[0.003991315,0.0003126316,0.001798759,0.001547476,0.0004130231,0.0005890289,0.001485361,0.0007679588,0.000497839],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006202485,"about_ca_system_score_gemma":0.0007101714,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003379881,"about_ca_topic_score_gemma":0.00398536,"domain_scores_codex":[0.9992053,0.0002837193,0.0000332328,0.0002668733,0.0001598788,0.0000511021],"domain_scores_gemma":[0.998133,0.001326123,0.0001333821,0.0002646695,0.00008595445,0.00005688187],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001209423,0.0001923352,0.2842077,0.001083784,0.006087729,0.001309096,0.0004857575,0.3854338,0.08390923,0.02591694,0.00987324,0.200291],"study_design_scores_gemma":[0.00005167333,0.0002151479,0.0679785,0.00006446226,0.0007228297,0.0004338988,0.000149891,0.8700792,0.01527005,0.02930398,0.01567726,0.00005304407],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.3726289,0.001962475,0.5906222,0.0006338563,0.00007381073,0.00008274526,0.0231681,0.00620887,0.004618919],"genre_scores_gemma":[0.8598328,0.0007441342,0.1167791,0.0002167262,0.00005441884,0.0002020729,0.01953409,0.0009867186,0.00164995],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.003379881,"threshold_uncertainty_score":0.01152635,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00522141975189719,"score_gpt":0.2458233643826702,"score_spread":0.2406019446307731,"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."}}