{"id":"W2052495959","doi":"10.1210/me.2004-0101","title":"Prediction of Nuclear Hormone Receptor Response Elements","year":2004,"lang":"en","type":"article","venue":"Molecular Endocrinology","topic":"Genomics and Chromatin Dynamics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":132,"is_retracted":false,"has_abstract":true,"ca_institutions":"Children's & Women's Health Centre of British Columbia; University of British Columbia","funders":"Canadian Institutes of Health Research","keywords":"Biology; Regulon; Computational biology; Nuclear receptor; Transcription factor; Markov chain; Identification (biology); Genetics; Bioinformatics; Gene; Computer science; Machine learning; Ecology","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":[0.00009486594,0.0001341806,0.0001443141,0.0000640293,0.00004349403,0.000006322392,0.0002016289,0.0001191926,0.00002047553],"category_scores_gemma":[0.00006854784,0.0001484427,0.00009123242,0.00006786093,0.00009538104,0.00000201669,0.0001492415,0.00007973909,0.00002568777],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000328066,"about_ca_system_score_gemma":0.00005902613,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000126751,"about_ca_topic_score_gemma":0.000002406221,"domain_scores_codex":[0.9989836,0.00007238414,0.0002790053,0.0002836243,0.00009847216,0.0002829158],"domain_scores_gemma":[0.9993733,0.000003923785,0.0001104932,0.0003934969,0.00006405683,0.00005474428],"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":[0.0003732746,0.00008699609,0.0002026235,0.000006284249,0.00007363317,0.0000136151,0.00003281626,0.000334374,0.9966128,0.00155734,0.0003047046,0.0004015725],"study_design_scores_gemma":[0.003282919,0.002313438,0.009156552,0.00001096687,0.00004001637,0.0001276488,0.0001241829,0.00007891177,0.9295858,0.0008545394,0.05415265,0.0002724157],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9965845,0.0003939715,0.001933004,0.0002977691,0.0001278045,0.0001476315,0.00006437206,0.00001834053,0.0004326],"genre_scores_gemma":[0.9940155,0.0002148409,0.00528112,0.0002131957,0.00003516524,0.00001214173,0.0001285161,0.00003243427,0.0000671485],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.067027,"threshold_uncertainty_score":0.6053317,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007038395392579395,"score_gpt":0.2136388893477766,"score_spread":0.2066004939551972,"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."}}