{"id":"W2145429131","doi":"10.1093/nar/gkt574","title":"DNA motif elucidation using belief propagation","year":2013,"lang":"en","type":"article","venue":"Nucleic Acids Research","topic":"Genomics and Chromatin Dynamics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":70,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; University of Toronto","keywords":"Hidden Markov model; Motif (music); Biology; Executable; Computational biology; DNA microarray; DNA; Computer science; Pattern recognition (psychology); Artificial intelligence; Genetics; Gene; Physics","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.002240949,0.001497882,0.001652404,0.002233974,0.0008274631,0.001486654,0.002643225,0.002026014,0.003463759],"category_scores_gemma":[0.009390306,0.001105194,0.001725822,0.001561885,0.001028733,0.001603305,0.001675716,0.003203254,0.0009578007],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00165917,"about_ca_system_score_gemma":0.002174452,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01150465,"about_ca_topic_score_gemma":0.01025224,"domain_scores_codex":[0.998991,0.0003041398,0.00006680886,0.0002941477,0.000225306,0.0001186667],"domain_scores_gemma":[0.9933079,0.005254247,0.0003362308,0.0002480811,0.0006971887,0.0001561632],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002499995,0.0001257719,0.0024153,0.0001639452,0.0001307818,0.0000991836,0.0001416571,0.795294,0.003394363,0.009092581,0.002386341,0.1865062],"study_design_scores_gemma":[0.000007533172,0.000007910311,0.00004474173,0.000004697193,0.000005210915,0.000006374799,0.000006391589,0.9957744,0.0005529866,0.00343568,0.0001496901,0.000004304734],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01157585,0.0001532676,0.9860838,0.0001898136,0.00002907173,0.00005757565,0.0001407042,0.001255151,0.0005148016],"genre_scores_gemma":[0.2610984,0.0002180786,0.7341341,0.0004190502,0.00007532095,0.0003920782,0.00105342,0.0002779363,0.002331616],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01150465,"threshold_uncertainty_score":0.02287537,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0302840214307884,"score_gpt":0.3100416049195864,"score_spread":0.279757583488798,"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."}}