{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004177578,0.0006818095,0.0005485119,0.0005625643,0.0002142764,0.0009328595,0.0007626943,0.0006379818,0.01933959],"category_scores_gemma":[0.002399211,0.0001491317,0.0003514368,0.001156806,0.0004252258,0.001385411,0.0004850331,0.0007612961,0.005942418],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005109724,"about_ca_system_score_gemma":0.0002923086,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001134203,"about_ca_topic_score_gemma":0.001331703,"domain_scores_codex":[0.9996475,0.0001132379,0.00001736997,0.0000477176,0.0001515739,0.00002251695],"domain_scores_gemma":[0.9992886,0.0003159727,0.00003908276,0.0001893625,0.0001411912,0.00002586952],"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":[0.0003570229,0.00007410397,0.000836611,0.0006455046,0.00007174058,0.0002086547,0.0001370128,0.1612551,0.02269622,0.2220167,0.03218297,0.5595183],"study_design_scores_gemma":[0.0000196974,0.0001618168,0.0003205042,0.00009267371,0.0000389956,0.0001735842,0.00003790206,0.8724434,0.009607939,0.04914786,0.06793442,0.00002119851],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01485542,0.004282791,0.9583421,0.001031536,0.0009357019,0.0001440421,0.0004398726,0.001296005,0.01867253],"genre_scores_gemma":[0.468881,0.01441222,0.4338387,0.000587319,0.001442386,0.0005017728,0.002600954,0.0006321465,0.0771036],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01933959,"threshold_uncertainty_score":0.06469738,"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."}}