{"id":"W2062872358","doi":"10.1101/gr.2589004","title":"Decoding Human Regulatory Circuits","year":2004,"lang":"en","type":"article","venue":"Genome Research","topic":"Genomics and Chromatin Dynamics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":107,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"National Human Genome Research Institute; Canadian Institutes of Health Research; National Institutes of Health; National Science Foundation","keywords":"Biology; Gene; Computational biology; DNA binding site; Gibbs sampling; Decoding methods; Genetics; Regulatory sequence; Upstream (networking); Transcription factor; Algorithm; Gene expression; Computer science; Promoter; Artificial intelligence","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":[0.0007222263,0.0001009385,0.00009471554,0.0001019987,0.0003232402,0.00005204511,0.0003567654,0.0001299403,0.00003921307],"category_scores_gemma":[0.00003975635,0.0001080733,0.00006269642,0.0001448197,0.000128104,0.000002121627,0.0002597404,0.000182842,0.0000936928],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001027459,"about_ca_system_score_gemma":0.0001676092,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002636855,"about_ca_topic_score_gemma":0.00004732316,"domain_scores_codex":[0.9986889,0.00005439674,0.0001610789,0.0003461928,0.0002700848,0.0004793885],"domain_scores_gemma":[0.9991842,0.000006218022,0.00002877188,0.0005096443,0.0001405667,0.0001306191],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.000003296341,0.00003709669,0.0003549719,0.00001845761,0.00002115024,0.000007175853,0.00006845741,0.0003760366,0.9956877,0.002402748,0.000124248,0.0008987162],"study_design_scores_gemma":[0.005491641,0.002306886,0.1442205,0.0001075785,0.00003137336,0.0002361581,0.001357461,0.0001493577,0.6690868,0.04179823,0.1332411,0.001972994],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9901026,0.0006737362,0.0004794512,0.0001061251,0.00005055789,0.000158852,0.000008712058,0.00001150188,0.008408391],"genre_scores_gemma":[0.9976279,0.0001295789,0.0005125554,0.00004263376,0.0002765122,0.00001878923,0.00009292398,0.00003153804,0.001267598],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3266009,"threshold_uncertainty_score":0.4407101,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04576788832245875,"score_gpt":0.3401340361277617,"score_spread":0.294366147805303,"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."}}