{"id":"W1984734093","doi":"10.3389/fgene.2014.00431","title":"Pleiotropy constrains the evolution of protein but not regulatory sequences in a transcription regulatory network influencing complex social behaviors","year":2014,"lang":"en","type":"article","venue":"Frontiers in Genetics","topic":"Plant and animal studies","field":"Agricultural and Biological Sciences","cited_by":38,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"Ontario Ministry of Research and Innovation; Natural Sciences and Engineering Research Council of Canada; York University","keywords":"Biology; Genetics; Gene regulatory network; Gene; Noncoding DNA; Conserved sequence; Pleiotropy; Regulatory sequence; Transcription factor; Negative selection; Evolutionary biology; Social connectedness; Molecular evolution; Computational biology; Phenotype; Phylogenetics; Genome; Gene expression; Peptide sequence","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":[0.0003753519,0.0001161535,0.0002164779,0.00001894083,0.0001852631,0.00001460401,0.0001937662,0.0001060859,0.000006293489],"category_scores_gemma":[0.00001319228,0.00005250644,0.00006125837,0.0002501233,0.0003469854,0.00003985496,0.00002799073,0.0001283054,5.062128e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001017179,"about_ca_system_score_gemma":0.00001683883,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00034514,"about_ca_topic_score_gemma":0.003725186,"domain_scores_codex":[0.9988973,0.0001557996,0.0002976419,0.0001802972,0.0002063074,0.0002626998],"domain_scores_gemma":[0.9997714,0.00002680732,0.000118291,0.00002754189,0.0000315632,0.00002440949],"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":[0.00005200387,0.00003123024,0.3455355,0.00001109026,0.000008087653,9.17538e-7,0.0004364375,0.0002863607,0.6411436,0.0007583042,0.0004803853,0.01125607],"study_design_scores_gemma":[0.0001480087,0.0001064422,0.9931696,0.00004095488,0.00001016202,8.592913e-7,0.001723183,0.0006858265,0.001870892,0.001311193,0.0008096813,0.0001231849],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9985898,0.0005907915,0.00006430523,0.0002205843,0.0001221591,0.0002663418,0.00002693806,0.00001551364,0.0001035448],"genre_scores_gemma":[0.9989156,0.0000345526,0.0007552083,0.00004280575,0.000201347,0.00001709353,0.000007924777,0.000001057712,0.00002446114],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6476341,"threshold_uncertainty_score":0.2141151,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03031493370728446,"score_gpt":0.2064024380430289,"score_spread":0.1760875043357444,"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."}}