{"id":"W2100224524","doi":"10.1109/dcc.2004.1281519","title":"Efficient side-information context description for context-based adaptive entropy coders","year":2004,"lang":"en","type":"article","venue":"","topic":"Advanced Data Compression Techniques","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Computer science; Entropy (arrow of time); Context model; Data compression; Quantization (signal processing); Entropy encoding; Adaptive coding; Cluster analysis; Algorithm; Artificial intelligence; Lossless compression","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":[0.0001929383,0.00016772,0.0001689669,0.0001536302,0.0001653709,0.0001526057,0.0005658429,0.0000664978,0.000009869368],"category_scores_gemma":[0.00009366315,0.0001445877,0.00008378721,0.0001848108,0.00005916926,0.001150914,0.0001110731,0.00008855664,0.00006108905],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002343235,"about_ca_system_score_gemma":0.0001242032,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000816063,"about_ca_topic_score_gemma":0.00002104517,"domain_scores_codex":[0.99878,0.00002907246,0.0003484963,0.0002766577,0.000285015,0.0002807714],"domain_scores_gemma":[0.9988215,0.0001188832,0.0001878293,0.0004925792,0.0002803235,0.00009890513],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001248263,0.0001120233,0.000004555872,0.00001602687,0.000009908713,0.000001458443,0.0004988628,0.03473172,0.003680502,0.8412526,0.002629816,0.1169377],"study_design_scores_gemma":[0.00267624,0.0004268142,0.00004334478,0.00007590903,0.000006535573,0.00000421123,0.000439512,0.7485163,0.2158396,0.01854922,0.01309011,0.0003322151],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.001143597,0.00003200225,0.9956501,0.0008703963,0.0002155577,0.0008950821,0.00003246678,0.0007650208,0.0003957484],"genre_scores_gemma":[0.6456863,0.000001084237,0.3523476,0.001783644,0.00001019559,0.0001180083,0.0000263183,0.000005184343,0.00002164042],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8227034,"threshold_uncertainty_score":0.5896116,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02478864828566574,"score_gpt":0.2605059585756771,"score_spread":0.2357173102900114,"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."}}