{"id":"W2294802772","doi":"10.1007/978-3-642-21204-8_9","title":"An Improved Approximation Algorithm for the Complementary Maximal Strip Recovery Problem","year":2011,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Genome Rearrangement Algorithms","field":"Biochemistry, Genetics and Molecular Biology","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Substring; Approximation algorithm; Combinatorics; Algorithm; STRIPS; Sequence (biology); Set (abstract data type); Mathematics; Computer science; Discrete mathematics","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":[0.001424818,0.001724067,0.002417648,0.001541231,0.001229615,0.002830614,0.004791755,0.002474615,0.01619672],"category_scores_gemma":[0.00545871,0.0008992057,0.001874202,0.003503645,0.001141028,0.004566192,0.003930158,0.004083944,0.003469818],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001625657,"about_ca_system_score_gemma":0.002829558,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004484992,"about_ca_topic_score_gemma":0.005411905,"domain_scores_codex":[0.9983684,0.0003063167,0.00009036829,0.0003904949,0.0005209769,0.000323463],"domain_scores_gemma":[0.9972186,0.001388826,0.0001383907,0.0007725597,0.0003188921,0.0001626829],"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":[0.001299873,0.000810252,0.0009005956,0.0005932271,0.0001516866,0.0002460582,0.000315555,0.2205858,0.01178099,0.08199736,0.04862532,0.6326933],"study_design_scores_gemma":[0.0003118089,0.0001288675,0.0003025205,0.00003439555,0.00006876279,0.000190702,0.0001213745,0.909258,0.003130689,0.07930993,0.007109911,0.00003298878],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02303554,0.0004177046,0.9618227,0.0006728061,0.0002234931,0.0002608278,0.0005507608,0.00258051,0.01043552],"genre_scores_gemma":[0.09453342,0.0002710053,0.8956209,0.0002567745,0.0001613112,0.0003709704,0.00174858,0.0005137532,0.006523219],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01619672,"threshold_uncertainty_score":0.05418342,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01830877909192158,"score_gpt":0.2418201984733534,"score_spread":0.2235114193814318,"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."}}