{"id":"W2122261046","doi":"10.1093/molbev/mst053","title":"Gene Coexpression Networks Reveal Key Drivers of Phenotypic Divergence in Lake Whitefish","year":2013,"lang":"en","type":"article","venue":"Molecular Biology and Evolution","topic":"Bioinformatics and Genomic Networks","field":"Biochemistry, Genetics and Molecular Biology","cited_by":119,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"U.S. Geological Survey; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs; National Park Service; University of Victoria","keywords":"Biology; Transcriptome; Evolutionary biology; Gene; Gene regulatory network; Phenotype; Ecotype; Ecology; Computational biology; Genetics; Gene expression","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":[0.000142955,0.0001246896,0.0001495979,0.00004834748,0.00005194598,0.000006574228,0.0001164696,0.0003073088,0.000023568],"category_scores_gemma":[0.00002014227,0.0001165021,0.00004618831,0.00008584863,0.0001458196,0.000006531422,0.0001435304,0.000106935,0.000004297856],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001003153,"about_ca_system_score_gemma":0.00002006402,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004984968,"about_ca_topic_score_gemma":0.00009042052,"domain_scores_codex":[0.9991804,0.00007091223,0.0002455638,0.0002253102,0.00004241196,0.0002354493],"domain_scores_gemma":[0.9995821,0.000006419572,0.0001040063,0.000194359,0.00005577024,0.00005736957],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.00008134963,0.00005374163,0.1883026,0.00002559029,0.00005035827,0.000001664374,0.00009317727,0.003487594,0.7995413,0.001267981,0.001828029,0.005266692],"study_design_scores_gemma":[0.003918434,0.00142775,0.833908,0.0001813861,0.00008940716,0.00005329222,0.000296511,0.0414979,0.0919723,0.02036635,0.004919617,0.00136909],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.913203,0.001660355,0.0843873,0.00006499539,0.0001394057,0.0001939434,0.00001389643,0.000005556791,0.0003315335],"genre_scores_gemma":[0.9977063,0.0002612392,0.001572193,0.0001447591,0.00005220782,0.00001672063,0.0001715924,0.000007669452,0.00006735092],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7075689,"threshold_uncertainty_score":0.475082,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003454457548263872,"score_gpt":0.2060965530341091,"score_spread":0.2026420954858452,"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."}}