{"id":"W2139000699","doi":"10.1145/2338626.2338633","title":"Reordering rows for better compression","year":2012,"lang":"en","type":"article","venue":"ACM Transactions on Database Systems","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":30,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of New Brunswick","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Speedup; Lexicographical order; Row; Sorting; Compression (physics); Algorithm; Data compression; Heuristic; Heuristics; Huffman coding; Compression ratio; Encoding (memory); Parallel computing; Mathematics; Combinatorics; Artificial intelligence; Database","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":[0.0004722758,0.0002371075,0.0002726967,0.0001542237,0.0004377103,0.00007377272,0.0006301859,0.00006882168,0.00001767138],"category_scores_gemma":[0.00004469308,0.0002044488,0.0001031192,0.0002472866,0.00003286566,0.002033568,0.00004848178,0.0001769014,0.000117284],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006316912,"about_ca_system_score_gemma":0.00002581417,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001104774,"about_ca_topic_score_gemma":0.00001256705,"domain_scores_codex":[0.9982471,0.0001012953,0.0003955039,0.000430374,0.0002965519,0.0005291668],"domain_scores_gemma":[0.9972442,0.0003068764,0.0001280144,0.002045617,0.00006650452,0.0002088077],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0004505993,0.002755681,0.00102,0.003893941,0.0007478192,0.00005142975,0.005046713,0.01662073,0.08558463,0.4106841,0.0618893,0.411255],"study_design_scores_gemma":[0.0008524553,0.0001007479,0.00006792793,0.0004419422,0.0000265961,0.00008866107,0.0002477753,0.01235291,0.01169595,0.00006860908,0.9735073,0.0005491019],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.001124852,0.0005091833,0.9932705,0.0002775919,0.002815309,0.0006810279,0.0007584566,0.0003009638,0.0002620797],"genre_scores_gemma":[0.520099,0.00005060507,0.476923,0.0003228357,0.0006335341,0.0008706806,0.0002444571,0.00005681237,0.0007990473],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.911618,"threshold_uncertainty_score":0.8337182,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04066127576892296,"score_gpt":0.289049769394661,"score_spread":0.248388493625738,"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."}}