{"id":"W1523223925","doi":"10.1109/dcc.1995.515576","title":"Bitgroup modeling of signal data for image compression","year":2002,"lang":"en","type":"article","venue":"","topic":"Algorithms and Data Compression","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Gray code; Lossless compression; Algorithm; Binary number; Computer science; Data compression; Bit plane; Binary data; Hamming distance; Binary code; Hamming code; Arithmetic coding; Context-adaptive binary arithmetic coding; Mathematics; Decoding methods; Arithmetic; Block code; Bit field","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":[0.0001692548,0.00008247406,0.0001284238,0.0000481028,0.00008682191,0.0000652243,0.001702406,0.00003346401,0.0001128967],"category_scores_gemma":[0.0000146216,0.00006108666,0.00003025915,0.0001060238,0.00001758454,0.001152637,0.001254324,0.00004988836,0.00001402788],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000004614541,"about_ca_system_score_gemma":0.000007324847,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003485606,"about_ca_topic_score_gemma":9.830289e-7,"domain_scores_codex":[0.999065,0.00001744201,0.0002096235,0.0003540796,0.0001943689,0.0001595317],"domain_scores_gemma":[0.9985446,0.00007310883,0.00005924436,0.001198245,0.00006972053,0.00005511692],"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":[0.00004027553,0.001030082,0.00005138044,0.0002071869,0.00005526606,0.00001664323,0.0005349251,0.01419186,0.06894843,0.05110504,0.2617532,0.6020657],"study_design_scores_gemma":[0.000277867,0.00003802215,0.000003454186,0.00002751872,0.000002815922,0.000002953509,0.000007862137,0.9941832,0.001347375,0.0011498,0.002872081,0.0000869888],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0003840705,0.0001776976,0.9972894,0.0001642272,0.0001051493,0.0001254128,0.00006547131,0.00007536402,0.001613265],"genre_scores_gemma":[0.2242311,0.00002254923,0.7753618,0.00007896197,0.00006381221,0.000004644054,0.00006162131,0.000006335491,0.0001692644],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9799914,"threshold_uncertainty_score":0.3163523,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1054832640724773,"score_gpt":0.2927010384008144,"score_spread":0.1872177743283371,"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."}}