{"id":"W2118596665","doi":"10.1093/bioinformatics/btk027","title":"ORegAnno: an open access database and curation system for literature-derived promoters, transcription factor binding sites and regulatory variation","year":2006,"lang":"en","type":"article","venue":"Bioinformatics","topic":"Genomics and Chromatin Dynamics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":123,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canada's Michael Smith Genome Sciences Centre","funders":"Genome British Columbia; Genome Canada","keywords":"Ensembl; Annotation; License; Database; Transcription factor; dbSNP; Computer science; DNA binding site; Promoter; World Wide Web; Computational biology; Biology; Gene; Bioinformatics; Genetics; Genomics; Genotype","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":[0.0001591114,0.0001332841,0.000115047,0.00005210027,0.0001739965,0.0007647899,0.0001884508,0.0001214119,7.68115e-7],"category_scores_gemma":[0.00001330314,0.0001237566,0.00001807599,0.00005358854,0.00002749211,0.0002103145,0.0001179511,0.00003497247,3.216008e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002379663,"about_ca_system_score_gemma":0.00003444062,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000142581,"about_ca_topic_score_gemma":0.00003959917,"domain_scores_codex":[0.999339,0.00001971493,0.0002726846,0.0001726983,0.00006689849,0.0001289845],"domain_scores_gemma":[0.999487,0.000006168468,0.0001699136,0.0002076393,0.00007861199,0.00005059822],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00005367113,0.00002802757,0.0005189415,0.0005749418,0.00001951738,2.692003e-7,0.0005310202,0.000033374,0.9958342,0.001099171,0.0001155336,0.001191347],"study_design_scores_gemma":[0.00576709,0.001395228,0.06036907,0.0005403702,0.0002040811,0.0001136271,0.001455987,0.5470868,0.3776911,0.0007757561,0.003032512,0.001568295],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9654461,0.0001340511,0.03305119,0.0000273551,0.00008032397,0.0006797954,0.0005077546,0.00001688662,0.00005660484],"genre_scores_gemma":[0.9741091,0.00005509414,0.02059906,0.00002675341,0.00009341374,0.00003039537,0.005032782,0.0000162678,0.00003710188],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.618143,"threshold_uncertainty_score":0.7374887,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01912677982166692,"score_gpt":0.2672365525115915,"score_spread":0.2481097726899246,"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."}}