{"id":"W2105768287","doi":"10.1109/dcc.2008.25","title":"List Update Algorithms for Data Compression","year":2008,"lang":"en","type":"article","venue":"DCC","topic":"Algorithms and Data Compression","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Algorithm; Data compression; Locality of reference; Compression (physics); Locality; Subroutine; Construct (python library); Compression ratio; Parallel computing; Cache; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001807201,0.0001246466,0.0001507158,0.00004816999,0.0003642355,0.00009158457,0.002419545,0.00005321487,0.00002504259],"category_scores_gemma":[0.00002975208,0.0001002289,0.00003570477,0.0001512927,0.0000466912,0.0010572,0.001684869,0.00009157885,0.00007455314],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001163785,"about_ca_system_score_gemma":0.00004826866,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005848381,"about_ca_topic_score_gemma":0.000002549711,"domain_scores_codex":[0.9987343,0.00002754086,0.0001870389,0.0005485554,0.0002433969,0.0002591535],"domain_scores_gemma":[0.9978346,0.00007453086,0.00007573946,0.001843931,0.00006264932,0.000108533],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002017989,0.0001971765,0.0002964564,0.00002278211,0.0000197614,0.00006306855,0.000225502,0.00002896994,0.001020377,0.00884255,0.6870183,0.3022449],"study_design_scores_gemma":[0.0003514511,0.00002869639,0.000477377,0.00001656791,0.000002521641,0.00003449752,0.000002488919,0.5009108,0.0005413428,0.0007520164,0.4967464,0.0001358544],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0009388801,0.0003455367,0.996271,0.0006654498,0.000706366,0.0001844407,0.0001748529,0.0001901627,0.0005233317],"genre_scores_gemma":[0.03304926,0.0002352113,0.9628595,0.001044233,0.0005555536,0.00003046357,0.001243332,0.00002397922,0.0009585057],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.5008818,"threshold_uncertainty_score":0.4496157,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1267360926996233,"score_gpt":0.3246432032365211,"score_spread":0.1979071105368978,"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."}}