{"id":"W2951833220","doi":"10.1007/978-1-4939-2864-4_73","title":"Closest String and Substring Problems","year":2016,"lang":"en","type":"book-chapter","venue":"Encyclopedia of Algorithms","topic":"Algorithms and Data Compression","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Western University; University of Waterloo","funders":"","keywords":"Substring; Combinatorics; Hamming distance; String (physics); Approximate string matching; String searching algorithm; Mathematics; Edit distance; Discrete mathematics; Logarithm; Set (abstract data type); Algorithm; Pattern matching; Computer science; Artificial intelligence","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":[0.0007594871,0.001297695,0.001889523,0.002513019,0.001072619,0.00353752,0.002309525,0.00240384,0.0258719],"category_scores_gemma":[0.005774557,0.0005441072,0.0009209807,0.00808962,0.002014769,0.007159673,0.002913916,0.003890783,0.01130531],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001214796,"about_ca_system_score_gemma":0.001251909,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005951546,"about_ca_topic_score_gemma":0.0005327257,"domain_scores_codex":[0.9983334,0.0002706308,0.0001185584,0.0003410641,0.0008717301,0.00006459114],"domain_scores_gemma":[0.9988494,0.000597022,0.00007540744,0.0002747688,0.0001504207,0.00005306083],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00005585658,0.00006493154,0.000167484,0.0007756298,0.00003165274,0.0001176668,0.0001320526,0.01094691,0.0008597259,0.4641339,0.08117647,0.4415376],"study_design_scores_gemma":[0.00001329055,0.00002002813,0.0001008533,0.0001268881,0.00001260221,0.0003744699,0.00004275758,0.01311712,0.0005445424,0.9007297,0.08490294,0.00001480885],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00910053,0.06667147,0.6234804,0.006317574,0.005191707,0.0001611319,0.001382834,0.001561916,0.2861325],"genre_scores_gemma":[0.1219053,0.08396705,0.5292763,0.002055428,0.009490544,0.0005346463,0.007013054,0.001668683,0.244089],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.0258719,"threshold_uncertainty_score":0.08655012,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01393923514751617,"score_gpt":0.2182260767107492,"score_spread":0.204286841563233,"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."}}