{"id":"W1964432965","doi":"10.1016/j.tcs.2014.09.003","title":"Less space: Indexing for queries with wildcards","year":2014,"lang":"en","type":"article","venue":"Theoretical Computer Science","topic":"Algorithms and Data Compression","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Substring; Search engine indexing; Combinatorics; String (physics); Mathematics; Character (mathematics); Set (abstract data type); Space (punctuation); Alphabet; Upper and lower bounds; Computer science; Discrete mathematics; Information retrieval","routes":{"ca_aff":true,"ca_fund":true,"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":[0.001343437,0.0001886286,0.0002201208,0.000122999,0.0006253521,0.0006766955,0.00228853,0.00004600395,0.000004290329],"category_scores_gemma":[0.00007522884,0.000127622,0.00004459063,0.0006534213,0.001958416,0.001047303,0.001062505,0.0001392166,0.000008370786],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003223755,"about_ca_system_score_gemma":0.0001206681,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005267127,"about_ca_topic_score_gemma":9.28049e-7,"domain_scores_codex":[0.9977708,0.00006534742,0.0001802353,0.0007576666,0.000654713,0.0005712123],"domain_scores_gemma":[0.9981872,0.000315434,0.0000694089,0.0009543253,0.0002266693,0.0002470017],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001116115,0.00001982154,0.00006014248,0.000007342534,0.000002011549,0.00000144493,0.0001668765,0.0001965172,0.0001169298,0.8948182,0.00007470358,0.1045249],"study_design_scores_gemma":[0.0003620817,0.0004568212,0.0005739342,0.00005862064,0.000003723129,0.00002934182,0.00001258309,0.8660874,0.003057863,0.1264914,0.002597908,0.0002684161],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01107648,0.00001209257,0.9852542,0.001032006,0.0004394557,0.0001903596,0.000002398192,0.0002130094,0.00178002],"genre_scores_gemma":[0.5655341,8.517425e-7,0.4339766,0.0003169244,0.0001453353,0.00001063785,9.163564e-7,0.00000625801,0.0000083576],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8658909,"threshold_uncertainty_score":0.7215864,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008467994323228173,"score_gpt":0.2380903630094993,"score_spread":0.2296223686862712,"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."}}