{"id":"W4230719382","doi":"10.1145/1109557.1109603","title":"Implicit dictionaries with <i>O</i>(1) modifications per update and fast search","year":2006,"lang":"en","type":"article","venue":"Proceedings of the seventeenth annual ACM-SIAM symposium on Discrete algorithm - SODA '06","topic":"Natural Language Processing Techniques","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Conjecture; Constant (computer programming); Computer science; Set (abstract data type); Order (exchange); Combinatorics; Binary logarithm; Search cost; Search problem; Mathematics; Discrete mathematics; Theoretical computer science; Algorithm; Programming language","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":[0.001287559,0.0008250035,0.001618174,0.0005995124,0.0009706671,0.002829825,0.003382086,0.001841021,0.005918453],"category_scores_gemma":[0.01587225,0.001118745,0.0007672643,0.002387487,0.002397555,0.0155864,0.003607992,0.002519149,0.003649771],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001040319,"about_ca_system_score_gemma":0.00181221,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001208216,"about_ca_topic_score_gemma":0.002281119,"domain_scores_codex":[0.9974408,0.0004207319,0.0002908411,0.0005325213,0.000878884,0.0004361859],"domain_scores_gemma":[0.9824473,0.006781947,0.002092816,0.007422042,0.000903982,0.0003519097],"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":[0.003270603,0.0006325871,0.006238894,0.001340736,0.0001294785,0.0005587483,0.001427685,0.1251881,0.04642679,0.2290077,0.03010303,0.5556756],"study_design_scores_gemma":[0.0007259132,0.001592817,0.002973864,0.000254882,0.0001778633,0.00235789,0.0006197913,0.6092141,0.05825653,0.2797224,0.04389153,0.0002124402],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1613961,0.001796008,0.8135396,0.00198318,0.0003070269,0.0002951159,0.0007329882,0.003557757,0.01639222],"genre_scores_gemma":[0.4531761,0.0008124901,0.5263714,0.0006517754,0.0004369874,0.0004486859,0.001189239,0.0008119656,0.01610132],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.005918453,"threshold_uncertainty_score":0.01979917,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00571366836197134,"score_gpt":0.2340760520787537,"score_spread":0.2283623837167824,"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."}}