{"id":"W2066349684","doi":"10.1142/s0219720005001296","title":"MULTIPLE RNA STRUCTURE ALIGNMENT","year":2005,"lang":"en","type":"article","venue":"Journal of Bioinformatics and Computational Biology","topic":"RNA and protein synthesis mechanisms","field":"Biochemistry, Genetics and Molecular Biology","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University; University Health Network","funders":"","keywords":"RNA; String (physics); Algorithm; Structural alignment; Nucleic acid structure; Computer science; Sequence (biology); Multiple sequence alignment; Mathematics; Sequence alignment; Gene; Genetics; Biology; Peptide sequence","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001586879,0.00008711006,0.0001291676,0.00005304242,0.00005138864,0.00001728277,0.00009947176,0.00009412829,0.00002059587],"category_scores_gemma":[0.00004233079,0.0000652762,0.00005599935,0.00002604965,0.00004306921,0.000008507473,0.00004226799,0.00005500318,0.000002818409],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000007828752,"about_ca_system_score_gemma":0.00004696477,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":6.169782e-7,"about_ca_topic_score_gemma":0.000001390961,"domain_scores_codex":[0.9993669,0.00002636517,0.0003570197,0.00005932408,0.00008706484,0.000103324],"domain_scores_gemma":[0.9994699,0.00003056237,0.0002669888,0.00005958973,0.000108262,0.00006465734],"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":[0.0002903944,0.0001026427,0.002152797,0.00004724266,0.0003399782,0.000002799215,0.0004055699,0.01372476,0.6010029,0.006504667,0.002876952,0.3725494],"study_design_scores_gemma":[0.006054678,0.004561434,0.005578168,0.00009710723,0.0001192113,0.00176891,0.0006891547,0.05508953,0.5496151,0.03901859,0.3363741,0.001033919],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8997062,0.0008848663,0.09811699,0.0006960076,0.0001734385,0.00008678155,0.00003660905,0.000002860584,0.0002961814],"genre_scores_gemma":[0.9154523,0.0001175099,0.08357076,0.0005575687,0.0002436355,7.124063e-7,0.000030807,0.000004341517,0.00002234502],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3715154,"threshold_uncertainty_score":0.2661886,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007012230245182748,"score_gpt":0.2316625414116808,"score_spread":0.2246503111664981,"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."}}