{"id":"W2745257241","doi":"10.1093/bioinformatics/btx498","title":"Motif independent identification of potential RNA G-quadruplexes by G4RNA screener","year":2017,"lang":"en","type":"article","venue":"Bioinformatics","topic":"DNA and Nucleic Acid Chemistry","field":"Biochemistry, Genetics and Molecular Biology","cited_by":114,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Sherbrooke","funders":"Fonds de Recherche du Québec - Santé; Natural Sciences and Engineering Research Council of Canada; Fonds Québécois de la Recherche sur la Nature et les Technologies","keywords":"G-quadruplex; RNA; Computational biology; Nucleic acid structure; Computer science; Motif (music); Artificial intelligence; Biology; Genetics; Gene; DNA; Physics","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":[0.0001656438,0.0001268103,0.000126461,0.00001984864,0.0001658941,0.00008550996,0.0005089245,0.0001726486,0.00002395616],"category_scores_gemma":[0.00009070613,0.0001195227,0.00008996919,0.00001697461,0.0001465302,0.00002044225,0.0001994691,0.00006382888,0.0000212986],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000008309525,"about_ca_system_score_gemma":0.00003499423,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001597835,"about_ca_topic_score_gemma":0.000001849369,"domain_scores_codex":[0.9990749,0.000007161324,0.0004072459,0.0001297331,0.0002123619,0.0001686334],"domain_scores_gemma":[0.9985806,0.000002338181,0.0004948804,0.0007599255,0.00009151326,0.0000707361],"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":[0.00002357539,0.00004323625,0.0006532941,0.00006116168,0.00004271594,5.048607e-7,0.00003550857,0.00001642528,0.9823726,0.00002747936,0.01011879,0.006604744],"study_design_scores_gemma":[0.0004152826,0.00004432656,0.003084337,0.00001202106,0.00002417668,0.000007000608,0.0001230862,0.001467918,0.9884934,0.00003028141,0.006142501,0.0001556799],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9864158,0.00012739,0.00773848,0.00009888817,0.0001895386,0.00009716078,0.0001251797,0.00001089383,0.005196649],"genre_scores_gemma":[0.9962898,0.0001384972,0.001197634,0.0000492976,0.0001120116,0.000004254092,0.0002486578,0.00001310127,0.001946709],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009874018,"threshold_uncertainty_score":0.4873993,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007000891683450851,"score_gpt":0.2365385259042153,"score_spread":0.2295376342207644,"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."}}