{"id":"W2067194564","doi":"10.1016/s0022-0000(02)00004-1","title":"The longest common subsequence problem for sequences with nested arc annotations","year":2002,"lang":"en","type":"article","venue":"Journal of Computer and System Sciences","topic":"RNA and protein synthesis mechanisms","field":"Biochemistry, Genetics and Molecular Biology","cited_by":76,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Longest common subsequence problem; Combinatorics; Sequence (biology); Subsequence; Computer science; Discrete mathematics; Nested set model; Mathematics; Matching (statistics); Algorithm; Theoretical computer science; Information retrieval; Genetics","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":[0.005669688,0.00124763,0.003435393,0.004882407,0.002523867,0.003560473,0.003856137,0.004943825,0.003612189],"category_scores_gemma":[0.03395538,0.001740241,0.002577451,0.008214023,0.002005584,0.01022578,0.002632116,0.00285526,0.001332363],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001484136,"about_ca_system_score_gemma":0.003864856,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004835728,"about_ca_topic_score_gemma":0.003752284,"domain_scores_codex":[0.9943842,0.00108912,0.0009547461,0.001651167,0.001472765,0.0004480546],"domain_scores_gemma":[0.9653525,0.02501033,0.00323574,0.002970361,0.002654547,0.0007765287],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.003367868,0.001027392,0.01368111,0.00391298,0.0008480039,0.004732906,0.001749478,0.4097577,0.02606517,0.09996508,0.02395527,0.4109371],"study_design_scores_gemma":[0.0002303909,0.000236643,0.001772222,0.0001868258,0.0001781798,0.001395852,0.0007962982,0.669811,0.008699869,0.3095979,0.007007705,0.00008711445],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1961623,0.003966931,0.7822583,0.002816836,0.0002790636,0.0003424654,0.008714657,0.003036358,0.002423111],"genre_scores_gemma":[0.3960565,0.002343548,0.5638454,0.0004139024,0.0006317776,0.0004300644,0.0307199,0.0009857839,0.004573142],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005669688,"threshold_uncertainty_score":0.02998453,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02383866729261915,"score_gpt":0.2456956519260933,"score_spread":0.2218569846334741,"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."}}