{"id":"W2041726559","doi":"10.1101/gr.6902","title":"Discovery of Regulatory Elements by a Computational Method for Phylogenetic Footprinting","year":2002,"lang":"en","type":"letter","venue":"Genome Research","topic":"Genomics and Phylogenetic Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":330,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; Defense Advanced Research Projects Agency; National Science Foundation","keywords":"Phylogenetic tree; Biology; Footprinting; Phylogenetic network; Computational biology; Phylogenetics; Conserved sequence; Computational phylogenetics; Function (biology); Evolutionary biology; Set (abstract data type); Genetics; Gene; Computer science; Base sequence","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001105563,0.0002803181,0.0003991238,0.0001772213,0.0001880497,0.00004817449,0.0005500405,0.0004744871,0.00001460791],"category_scores_gemma":[0.00008415619,0.0002902482,0.0002420302,0.0001353219,0.0002072874,5.507491e-7,0.0004834799,0.0004673,0.000003624557],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004840941,"about_ca_system_score_gemma":0.0001509332,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002314999,"about_ca_topic_score_gemma":0.000001853295,"domain_scores_codex":[0.9971629,0.0002814665,0.0005085917,0.0007539847,0.000576929,0.0007160716],"domain_scores_gemma":[0.9985121,0.0001928222,0.0002107702,0.0005534847,0.0004847551,0.00004604573],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00003724158,0.0000540532,0.0003522471,0.0004061644,0.0005200924,0.000003038131,0.0000425373,0.0002225227,0.6582977,0.00002548618,0.3380091,0.002029845],"study_design_scores_gemma":[0.0007269321,0.0006102081,0.001658045,0.00003053416,0.00004983385,0.000007182057,0.00005100608,0.0001780865,0.01788467,0.001263942,0.9770995,0.000440098],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7373409,0.07734009,0.07306293,0.08583812,0.001106166,0.009023529,0.01103201,0.00001872177,0.005237564],"genre_scores_gemma":[0.5647157,0.005572003,0.2668275,0.06957043,0.01815038,0.002968918,0.01191951,0.001116062,0.05915946],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.640413,"threshold_uncertainty_score":0.9999549,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05476859112072156,"score_gpt":0.3510958603509624,"score_spread":0.2963272692302408,"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."}}