{"id":"W4221128536","doi":"10.1038/s41586-022-04506-6","title":"The evolution, evolvability and engineering of gene regulatory DNA","year":2022,"lang":"en","type":"article","venue":"Nature","topic":"Evolution and Genetic Dynamics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":300,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"National Human Genome Research Institute; Howard Hughes Medical Institute","keywords":"Evolvability; Biology; Regulatory sequence; Computational biology; Genetics; Gene regulatory network; Natural selection; Robustness (evolution); Gene; Human evolutionary genetics; Regulation of gene expression; Selection (genetic algorithm); Gene expression; Computer science; Phylogenetics; Artificial intelligence","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":[0.0008425949,0.00025166,0.0002606803,0.0004816667,0.0003727821,0.000978391,0.0006694924,0.0006275546,0.0006064175],"category_scores_gemma":[0.002939598,0.0002883358,0.0002600657,0.0003488358,0.001939573,0.001234886,0.0005463923,0.00119031,0.0001866117],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009104026,"about_ca_system_score_gemma":0.0004325612,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004816332,"about_ca_topic_score_gemma":0.0004026892,"domain_scores_codex":[0.9996738,0.0001109239,0.0000149356,0.00006691411,0.0000951837,0.000038195],"domain_scores_gemma":[0.9992556,0.0004650948,0.00007383143,0.0001053233,0.00005648448,0.00004359915],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.000316975,0.0001183512,0.01091704,0.0002924511,0.00006928763,0.0004010579,0.0007258432,0.06925534,0.3398325,0.4549923,0.000478141,0.1226008],"study_design_scores_gemma":[0.000103296,0.0004631403,0.01486265,0.0001127092,0.00009522985,0.001769006,0.0005231731,0.1820288,0.3044173,0.4500448,0.0454629,0.0001171172],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9063425,0.005283554,0.07469247,0.001482594,0.0001047225,0.00002097609,0.00006799951,0.0001776176,0.01182757],"genre_scores_gemma":[0.9826333,0.002225709,0.01230556,0.0001022336,0.00003582158,0.00002046424,0.00004819981,0.00004833943,0.002580357],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.000978391,"threshold_uncertainty_score":0.006605446,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.001513324521813752,"score_gpt":0.1926401764286814,"score_spread":0.1911268519068676,"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."}}