{"id":"W2341424800","doi":"10.1093/nar/gkv1477","title":"A comprehensive comparison of general RNA–RNA interaction prediction methods","year":2015,"lang":"en","type":"article","venue":"Nucleic Acids Research","topic":"RNA and protein synthesis mechanisms","field":"Biochemistry, Genetics and Molecular Biology","cited_by":70,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Canadian Institutes of Health Research; Natural Sciences and Engineering Research Council of Canada; University of British Columbia; Michael Smith Health Research BC","keywords":"RNA; Biology; Computational biology; Protein secondary structure; Nucleic acid secondary structure; Nucleic acid structure; Transfer RNA; Non-coding RNA; Ribosomal RNA; Transcriptome; Genetics; Bioinformatics; Gene; Gene expression; 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":[0.001249447,0.0001188081,0.0002121487,0.0001314148,0.00009487008,0.00002977595,0.0002738479,0.0002104115,0.00005679883],"category_scores_gemma":[0.0003396785,0.0001105191,0.00008166328,0.0001830156,0.0001381688,0.00000990366,0.0002161246,0.0002463523,0.00003384412],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004689521,"about_ca_system_score_gemma":0.000104781,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008640698,"about_ca_topic_score_gemma":0.000003966362,"domain_scores_codex":[0.9977375,0.0008945279,0.0002931314,0.0003174915,0.0004628076,0.000294536],"domain_scores_gemma":[0.9986677,0.00005824548,0.00008938448,0.0004067455,0.0006219246,0.0001560151],"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":[0.0003083943,0.00008412071,0.0004351505,0.00002131777,0.00004665909,9.477916e-7,0.0002607796,0.00005894545,0.9364328,0.0001397023,0.007732885,0.0544783],"study_design_scores_gemma":[0.0003873392,0.0008979866,0.0003715048,0.00001774523,0.00000759144,0.000006497455,0.0009094476,0.001739791,0.9115735,0.0003680556,0.08363096,0.00008962282],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9693933,0.0008202412,0.02010005,0.000143955,0.0003751815,0.0003345658,0.00001713013,0.00001845799,0.008797116],"genre_scores_gemma":[0.9715658,0.00008344794,0.02670939,0.00002954322,0.0003497855,0.0000410337,0.00004461223,0.00002633004,0.001149994],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07589807,"threshold_uncertainty_score":0.4506839,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1467006754149399,"score_gpt":0.4509606103228793,"score_spread":0.3042599349079393,"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."}}