{"id":"W1914990675","doi":"10.1109/dcc.2006.4","title":"A Unified Framework for Lossless Image Set Compression","year":2006,"lang":"en","type":"article","venue":"","topic":"Advanced Data Compression Techniques","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta; University of Lethbridge","funders":"","keywords":"Lossless compression; Image compression; Computer science; Entropy encoding; Spanning tree; Redundancy (engineering); Centroid; Image (mathematics); Data compression; Lossy compression; Minimum spanning tree; Entropy (arrow of time); Algorithm; ENCODE; Scheme (mathematics); Graph; Artificial intelligence; Mathematics; Theoretical computer science; Image processing; Discrete mathematics","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":[0.0008001847,0.000567677,0.0007465709,0.001425117,0.0005052689,0.001204507,0.001731242,0.0006401064,0.003186387],"category_scores_gemma":[0.001527618,0.0002985699,0.0008016411,0.001283161,0.0009186894,0.00207223,0.001679709,0.001339168,0.001024914],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007265678,"about_ca_system_score_gemma":0.0006783766,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00112767,"about_ca_topic_score_gemma":0.00139639,"domain_scores_codex":[0.9993274,0.0001039035,0.00003742784,0.00006779232,0.0004237275,0.00003972218],"domain_scores_gemma":[0.9995471,0.0001099992,0.00003539609,0.000156305,0.0001214095,0.00002980186],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001538505,0.0001003502,0.0002363045,0.0003316253,0.0001017892,0.0003374618,0.0002070364,0.1570626,0.03679461,0.3904016,0.01045568,0.4038171],"study_design_scores_gemma":[0.00002517049,0.00012824,0.0001681157,0.00006392195,0.00003842198,0.0004736609,0.00003815084,0.8749188,0.01435022,0.08321873,0.02653443,0.00004225749],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001385496,0.0002252574,0.9969019,0.00007047188,0.00002540755,0.00003192415,0.00003077056,0.0003982689,0.0009306184],"genre_scores_gemma":[0.08479765,0.001096039,0.9098023,0.0001184245,0.0001558161,0.000198038,0.0002542829,0.0001785424,0.003398891],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.003186387,"threshold_uncertainty_score":0.01065946,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02242962522075121,"score_gpt":0.3223165000410087,"score_spread":0.2998868748202575,"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."}}