{"id":"W2949366051","doi":"10.1002/spe.2402","title":"Consistently faster and smaller compressed bitmaps with Roaring","year":2016,"lang":"en","type":"article","venue":"Software Practice and Experience","topic":"Algorithms and Data Compression","field":"Computer Science","cited_by":56,"is_retracted":false,"has_abstract":true,"ca_institutions":"Saint John Regional Hospital; Université TÉLUQ","funders":"","keywords":"Bitmap; Uncompressed video; Computer science; SPARK (programming language); Computer graphics (images); Data compression; Compression (physics); Algorithm; Artificial intelligence; Materials science","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":[0.0009191962,0.0007923039,0.000743167,0.001483876,0.0005417644,0.002236689,0.001809842,0.0007863112,0.007435939],"category_scores_gemma":[0.007661787,0.0004065332,0.0005469669,0.003792589,0.0007943586,0.005155224,0.001931245,0.001253996,0.003797281],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005910945,"about_ca_system_score_gemma":0.0006538164,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0012554,"about_ca_topic_score_gemma":0.001374437,"domain_scores_codex":[0.9983888,0.0001583648,0.0001967837,0.0002262816,0.0008997459,0.0001301095],"domain_scores_gemma":[0.9950659,0.001340165,0.0003260611,0.001848737,0.001289112,0.0001299413],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00104944,0.0002224652,0.002291376,0.0006379097,0.0001175204,0.0003710177,0.0008289182,0.0241966,0.0931358,0.03287145,0.03844262,0.8058347],"study_design_scores_gemma":[0.0002336895,0.0006896112,0.003477978,0.0002738435,0.0001522546,0.001677546,0.0007265087,0.3303269,0.4417176,0.04599357,0.1743894,0.0003410788],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1106361,0.004084453,0.8159954,0.001387756,0.0008378996,0.0002963929,0.001740404,0.04341338,0.02160822],"genre_scores_gemma":[0.3288226,0.001179763,0.6463009,0.0009753216,0.0002626013,0.0003681692,0.004595901,0.003802103,0.01369277],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007435939,"threshold_uncertainty_score":0.0248757,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01415806701289741,"score_gpt":0.2441551405037744,"score_spread":0.229997073490877,"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."}}