{"id":"W3208481717","doi":"10.1261/rna.078889.121","title":"RNALigands: a database and web server for RNA–ligand interactions","year":2021,"lang":"en","type":"article","venue":"RNA","topic":"RNA and protein synthesis mechanisms","field":"Biochemistry, Genetics and Molecular Biology","cited_by":38,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"China Scholarship Council; Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China; National Science Foundation","keywords":"RNA; Biology; Computational biology; Web server; Protein Data Bank (RCSB PDB); Small molecule; Structural motif; Nucleic acid structure; Protein secondary structure; Non-coding RNA; Riboswitch; Small RNA; Genetics; Gene; Computer science; Biochemistry","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":[0.0001029347,0.0000859471,0.0000883242,0.00001606,0.00009325342,0.00003599602,0.000062158,0.00005545915,0.0000487612],"category_scores_gemma":[0.00009687964,0.00008183593,0.00005635246,0.00003576603,0.00001866715,0.000005561503,0.00007264845,0.00003680037,0.000006250928],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000003830477,"about_ca_system_score_gemma":0.00005460749,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004783218,"about_ca_topic_score_gemma":0.00004940048,"domain_scores_codex":[0.99946,0.000023972,0.0001029169,0.0002334074,0.00005189127,0.0001278415],"domain_scores_gemma":[0.9995896,0.00001631241,0.00003600856,0.000237499,0.00005654526,0.00006403366],"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":[0.00004138824,0.00002393029,0.00004804109,0.00002571252,0.00003998937,0.000005506853,0.00001315817,6.762065e-7,0.9930133,0.0003500711,0.001937467,0.004500718],"study_design_scores_gemma":[0.0002702793,0.00004631008,0.00003826702,0.00002645601,0.00002184044,0.00003399098,0.0000442497,0.00002945488,0.8684459,0.0003029041,0.1306429,0.00009743123],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9915785,0.001573047,0.004525227,0.0005095144,0.000226772,0.0001431884,0.0001159666,0.000009479003,0.001318294],"genre_scores_gemma":[0.9912584,0.0004640683,0.002766879,0.0004343867,0.0002568498,0.00004435866,0.0001449208,0.00001704227,0.004613101],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1287054,"threshold_uncertainty_score":0.3337173,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01850533572213791,"score_gpt":0.2719244087551382,"score_spread":0.2534190730330003,"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."}}