{"id":"W3144940706","doi":"10.1007/978-1-0716-1307-8_1","title":"Advanced Design of Structural RNAs Using RNARedPrint","year":2012,"lang":"en","type":"book-chapter","venue":"Methods in molecular biology","topic":"RNA and protein synthesis mechanisms","field":"Biochemistry, Genetics and Molecular Biology","cited_by":4,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University","funders":"Agence Nationale de la Recherche","keywords":"RNA; Rational design; Computational biology; Computer science; Software; Nucleic acid structure; Biology; Genetics; Programming language","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":[0.0006296163,0.0009765401,0.0008583733,0.0002903664,0.0004275891,0.0009603694,0.001050182,0.0007145294,0.004269568],"category_scores_gemma":[0.0004654723,0.0006195442,0.0006875808,0.0002711686,0.0005558417,0.0009172902,0.0007976608,0.00201535,0.003220028],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006702502,"about_ca_system_score_gemma":0.0003903284,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001258623,"about_ca_topic_score_gemma":0.0002317467,"domain_scores_codex":[0.9996625,0.00005094287,0.00002011822,0.00008803348,0.000128749,0.00004971407],"domain_scores_gemma":[0.9998701,0.00004774192,0.0000159506,0.00002462055,0.00002276511,0.00001884485],"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":[0.0003469815,0.0001328764,0.0001403108,0.0007592582,0.00004308215,0.0003397681,0.0002146215,0.02529009,0.7223682,0.08886354,0.006421436,0.1550799],"study_design_scores_gemma":[0.0001074696,0.000469195,0.00007807858,0.00005136052,0.00003032887,0.0002694625,0.00003711533,0.03268776,0.8379807,0.02173652,0.1064841,0.00006786497],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.06015586,0.008342806,0.8953532,0.0006322328,0.001192248,0.0002664867,0.000408667,0.005561882,0.02808657],"genre_scores_gemma":[0.3230462,0.007404481,0.6275221,0.0008555466,0.0001944133,0.000791751,0.00111868,0.001512925,0.03755398],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.004269568,"threshold_uncertainty_score":0.01428312,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04845560541314748,"score_gpt":0.3733317654060868,"score_spread":0.3248761599929393,"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."}}