{"id":"W4409666529","doi":"10.7554/elife.92497.2","title":"Exploiting fluctuations in gene expression to detect causal interactions between genes","year":2025,"lang":"en","type":"preprint","venue":"eLife","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Gene; Gene expression; Genetics; Computational biology; Biology; Expression (computer science); Computer science","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002374621,0.0002821501,0.0003451271,0.000307064,0.0001097764,0.0000434357,0.0003577805,0.000267567,0.00002265002],"category_scores_gemma":[0.0001559585,0.0003154609,0.0002102281,0.0002412177,0.00002154156,0.000003002467,0.001182235,0.0003016105,0.00001888548],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007992665,"about_ca_system_score_gemma":0.0002186697,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007471489,"about_ca_topic_score_gemma":0.0004150642,"domain_scores_codex":[0.9981524,0.0001541478,0.0004681229,0.0007262105,0.000205803,0.0002933598],"domain_scores_gemma":[0.9987652,0.00003368784,0.0001468746,0.0007806159,0.0001436342,0.0001299278],"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":[0.00001967591,0.00002502799,0.01296709,0.00004340416,0.000214556,0.000003604686,0.0001173552,0.07245582,0.9023764,0.000002050053,0.002964235,0.008810788],"study_design_scores_gemma":[0.0001569633,0.00002634317,0.0123779,0.0001547317,0.0001070951,0.000001349281,0.00006093573,0.0003038688,0.9758247,0.0000639322,0.01054053,0.0003817035],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9642708,0.001075866,0.03334803,0.0001717517,0.000392152,0.0003250857,0.00009001214,0.00003055725,0.0002957611],"genre_scores_gemma":[0.9824834,0.0002473076,0.0137253,0.0001520968,0.001289221,0.0002318639,0.0008035474,0.00003135392,0.001035917],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07344826,"threshold_uncertainty_score":0.9999297,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0221352403998354,"score_gpt":0.3042662938550361,"score_spread":0.2821310534552007,"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."}}