{"id":"W2805355421","doi":"10.1016/j.biochi.2018.06.002","title":"G4RNA screener web server: User focused interface for RNA G-quadruplex prediction","year":2018,"lang":"en","type":"article","venue":"Biochimie","topic":"DNA and Nucleic Acid Chemistry","field":"Biochemistry, Genetics and Molecular Biology","cited_by":61,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université de Sherbrooke","funders":"Fonds de recherche du Québec – Nature et technologies; Natural Sciences and Engineering Research Council of Canada","keywords":"Bottleneck; Computer science; Interface (matter); Identification (biology); Focus (optics); Software deployment; RNA; Web server; World Wide Web; Computational biology; Biology; Operating system; The Internet; Embedded system; Genetics; 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":[0.0001296517,0.0001991929,0.0001363551,0.00002815148,0.00012321,0.00003398518,0.0002794124,0.0002570254,0.0000876629],"category_scores_gemma":[0.00006619962,0.0001870252,0.0001347127,0.00006867848,0.0001395593,0.000006646324,0.0001316439,0.00006768606,0.00004429093],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001877131,"about_ca_system_score_gemma":0.00006433758,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007502433,"about_ca_topic_score_gemma":0.0000219379,"domain_scores_codex":[0.998893,0.00001794113,0.0002137013,0.0004455586,0.0001228272,0.0003069334],"domain_scores_gemma":[0.9991783,0.000007666076,0.00008370855,0.0004772729,0.0001388827,0.0001141872],"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":[0.0002285879,0.0000531346,0.0006058393,0.00002392429,0.0000653384,3.830907e-7,0.00001392331,0.000002702213,0.9325237,0.00004083248,0.06475823,0.001683463],"study_design_scores_gemma":[0.0008228186,0.0003401501,0.0004724853,0.00001626458,0.0000257573,0.000005012287,0.00002103466,0.0001447604,0.7599092,0.00002896011,0.2380388,0.0001747657],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9902302,0.0002647629,0.004780945,0.0002734442,0.0004244908,0.0002181868,0.0001641453,0.00005569733,0.003588117],"genre_scores_gemma":[0.9897665,0.00005567894,0.002586914,0.0003542541,0.001599569,0.00003672688,0.0002093657,0.00004732237,0.005343702],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1732806,"threshold_uncertainty_score":0.7626666,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01222942949596277,"score_gpt":0.2534312844582852,"score_spread":0.2412018549623224,"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."}}