{"id":"W2145195191","doi":"10.1002/spe.2325","title":"Better bitmap performance with Roaring bitmaps","year":2015,"lang":"en","type":"article","venue":"Software Practice and Experience","topic":"Algorithms and Data Compression","field":"Computer Science","cited_by":159,"is_retracted":false,"has_abstract":true,"ca_institutions":"Saint John Regional Hospital; Université TÉLUQ; Université du Québec à Montréal","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Bitmap; Computer science; Encoding (memory); Compression (physics); Oracle; Data compression; Compression ratio; Parallel computing; Algorithm; Computer graphics (images); Artificial intelligence; Engineering; Programming language","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":[0.0002383254,0.0001466638,0.0001205683,0.00005339286,0.0002149292,0.0003179163,0.0004998901,0.00004450558,0.000004760724],"category_scores_gemma":[0.0002088221,0.0001073661,0.0000101474,0.0002735302,0.00008790059,0.0053246,0.0004834881,0.0001712923,0.00004463556],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002173391,"about_ca_system_score_gemma":0.00008305573,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008264626,"about_ca_topic_score_gemma":0.000001796797,"domain_scores_codex":[0.9987321,0.00003951997,0.0001389817,0.000435368,0.0003764058,0.0002775684],"domain_scores_gemma":[0.9988816,0.0001289354,0.0001023866,0.0005333729,0.0001514365,0.0002022243],"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":[0.0002415003,0.0002808107,0.04760084,0.00006622591,0.0000407927,0.0003318615,0.05265972,0.0002118279,0.000373018,0.003272197,0.005238773,0.8896824],"study_design_scores_gemma":[0.002866982,0.002351311,0.01452788,0.0004264241,0.00005166004,0.002523985,0.008756831,0.05902491,0.007319412,0.001648924,0.8983601,0.00214157],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2812159,0.0004780611,0.7150019,0.001604311,0.000292926,0.000117829,0.00000127068,0.0002749654,0.001012828],"genre_scores_gemma":[0.533895,0.00009398048,0.4641506,0.0016042,0.00009326728,0.00003737684,0.000002794991,0.00001062834,0.0001121026],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8931214,"threshold_uncertainty_score":0.4378264,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0231628126247053,"score_gpt":0.2617781121611502,"score_spread":0.2386152995364449,"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."}}