{"id":"W3041118201","doi":"10.1093/nar/gkaa583","title":"Augmented base pairing networks encode RNA-small molecule binding preferences","year":2020,"lang":"en","type":"article","venue":"Nucleic Acids Research","topic":"RNA and protein synthesis mechanisms","field":"Biochemistry, Genetics and Molecular Biology","cited_by":61,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Université du Québec à Montréal; Mila - Quebec Artificial Intelligence Institute","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; Genome Canada","keywords":"Computational biology; RNA; ENCODE; Biology; Decoy; Drug discovery; Computer science; Binding site; Representation (politics); Function (biology); Artificial intelligence; Theoretical computer science; Bioinformatics; Genetics; Gene","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008819575,0.0001854773,0.0001770735,0.00007532796,0.0002782446,0.0001064346,0.0006121138,0.0002371147,0.0002900244],"category_scores_gemma":[0.0004297361,0.0001722224,0.00009774756,0.0003227587,0.0001124455,0.000007273206,0.0004658671,0.000361979,0.0001257055],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002372987,"about_ca_system_score_gemma":0.00009850206,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002566822,"about_ca_topic_score_gemma":0.00001099034,"domain_scores_codex":[0.9976798,0.0004096589,0.000231134,0.0005994,0.0004268835,0.0006531301],"domain_scores_gemma":[0.9990507,0.00005275915,0.00005229641,0.0003887384,0.0001434735,0.0003120432],"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":[0.0001491927,0.00003413764,0.0006082275,0.00003123597,0.00004518287,0.00001877847,0.00009508267,0.0001251609,0.9849886,0.00009651333,0.001795966,0.01201192],"study_design_scores_gemma":[0.0003977495,0.0006572465,0.0001170722,0.0000484712,0.000008493452,0.000003666678,0.000322372,0.00423595,0.9842099,0.00008427289,0.009663681,0.000251112],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9759007,0.0006358326,0.01486913,0.0008950296,0.0000850306,0.0004284313,0.00001252664,0.00005162972,0.00712167],"genre_scores_gemma":[0.9959378,0.0003115052,0.002121821,0.0003000994,0.0004192429,0.00007324322,0.00004713297,0.00004763982,0.0007415652],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02003703,"threshold_uncertainty_score":0.7023023,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07898301961486447,"score_gpt":0.3094185789716188,"score_spread":0.2304355593567543,"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."}}