{"id":"W2171866929","doi":"10.1017/s0960129515000134","title":"Fast circular dictionary-matching algorithm","year":2015,"lang":"en","type":"article","venue":"Mathematical Structures in Computer Science","topic":"Algorithms and Data Compression","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"String searching algorithm; Matching (statistics); Computation; Algorithm; String (physics); Pattern matching; Space (punctuation); Mathematics; Combinatorics; Approximate string matching; Computer science; Discrete mathematics; Artificial intelligence; Statistics","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":[0.0006332675,0.0006138643,0.001243804,0.001690329,0.001052302,0.001226335,0.001726554,0.001323757,0.009041062],"category_scores_gemma":[0.003172331,0.0003950075,0.0006648062,0.002612029,0.0006071407,0.002016514,0.002002171,0.0007320333,0.004945606],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006653459,"about_ca_system_score_gemma":0.002100633,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002360664,"about_ca_topic_score_gemma":0.002859093,"domain_scores_codex":[0.9987003,0.0001259859,0.0001371005,0.0003704172,0.0004687203,0.0001974594],"domain_scores_gemma":[0.9988153,0.000215366,0.0001003779,0.0004058318,0.0004059371,0.00005725498],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0007452284,0.0001572769,0.001629872,0.0002330939,0.00006469167,0.0002475636,0.0001822289,0.04857311,0.03394474,0.02199343,0.01837165,0.8738571],"study_design_scores_gemma":[0.0001416195,0.0001961409,0.0008286127,0.00002986947,0.00004357204,0.0009007254,0.0001360921,0.9020497,0.04987875,0.0226577,0.02308586,0.00005133835],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01777829,0.0004175563,0.975575,0.0001496303,0.0001153006,0.0001180702,0.0003303722,0.002609281,0.002906424],"genre_scores_gemma":[0.1318658,0.0002731806,0.8584101,0.0001949428,0.00007188979,0.0001833588,0.001654634,0.0002632947,0.007082878],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009041062,"threshold_uncertainty_score":0.03024542,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02040349900912089,"score_gpt":0.2687050296310084,"score_spread":0.2483015306218875,"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."}}