{"id":"W2561599208","doi":"10.1093/bib/bbw120","title":"Design of RNAs: comparing programs for inverse RNA folding","year":2016,"lang":"en","type":"review","venue":"Briefings in Bioinformatics","topic":"RNA and protein synthesis mechanisms","field":"Biochemistry, Genetics and Molecular Biology","cited_by":86,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Agence Nationale de la Recherche","keywords":"Nucleic acid secondary structure; RNA; Computer science; Folding (DSP implementation); Computational biology; Preprocessor; Inverse; Synthetic biology; Theoretical computer science; Artificial intelligence; Biology; Mathematics; Engineering; Genetics; Gene","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002081237,0.001183323,0.0007975054,0.001222514,0.0004717975,0.001066766,0.001587904,0.00123218,0.004969042],"category_scores_gemma":[0.006210588,0.0004430062,0.001191128,0.001412289,0.0004564634,0.00118586,0.001091407,0.001294605,0.001614466],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007980369,"about_ca_system_score_gemma":0.00103515,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001416982,"about_ca_topic_score_gemma":0.001579307,"domain_scores_codex":[0.998714,0.0005362997,0.0001056691,0.0002088147,0.0003276718,0.0001076045],"domain_scores_gemma":[0.996583,0.002664996,0.000109035,0.0002302691,0.0003459889,0.00006667726],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001755649,0.0006368661,0.00616002,0.003599658,0.0004243941,0.000198974,0.0004399186,0.3031666,0.01404036,0.04740271,0.02248357,0.5996912],"study_design_scores_gemma":[0.0003438652,0.0007060412,0.002012796,0.0004219313,0.0002122186,0.0002542774,0.0002286181,0.8522817,0.03269441,0.0293321,0.08142268,0.00008933913],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"review","genre_scores_codex":[0.1528821,0.01141849,0.765897,0.0008224852,0.0005821545,0.0005718564,0.002458786,0.02811279,0.03725437],"genre_scores_gemma":[0.218216,0.006370647,0.7530996,0.0005107665,0.00009928388,0.00165066,0.006182996,0.006759108,0.007111005],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.004969042,"threshold_uncertainty_score":0.01662308,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0747232420419325,"score_gpt":0.3053770490699766,"score_spread":0.2306538070280442,"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."}}