{"id":"W4402916713","doi":"10.1109/icip51287.2024.10648249","title":"Learned Compression of Encoding Distributions","year":2024,"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":"Encoding (memory); Computer science; Compression (physics); Data compression; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001005448,0.00005162115,0.00006934879,0.00005037953,0.00006391433,0.0000977765,0.0003678651,0.0000250686,0.00007551746],"category_scores_gemma":[0.00001208855,0.00003617155,0.00003788935,0.000251807,0.0000199267,0.0004258753,0.0003375191,0.0000698627,0.00004562669],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001060889,"about_ca_system_score_gemma":0.00002852938,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002542908,"about_ca_topic_score_gemma":5.681507e-7,"domain_scores_codex":[0.9994351,0.00001833617,0.000122375,0.0001857671,0.0001390857,0.000099389],"domain_scores_gemma":[0.9995551,0.00007398671,0.00001710367,0.000287961,0.00002586938,0.00004001345],"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":[0.000001285275,0.00003801108,0.00005576694,0.00003422773,0.000008402953,0.00001205956,0.0001342432,0.00004910105,0.02125398,0.7912698,0.0137476,0.1733955],"study_design_scores_gemma":[0.0001033512,0.00004345807,0.0006513502,0.0002146118,0.000004473199,0.00001388727,0.00001893596,0.8577369,0.03822634,0.01429244,0.088562,0.0001322558],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.001267825,0.0003887583,0.9899959,0.0004755301,0.0003502104,0.00003556766,0.0000121087,0.000222173,0.007251901],"genre_scores_gemma":[0.9448026,0.00003475056,0.05455191,0.00001844491,0.00003665953,0.000002603287,0.00001579971,0.000002855829,0.0005343226],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9435349,"threshold_uncertainty_score":0.1475033,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0297064461025144,"score_gpt":0.2981554495130548,"score_spread":0.2684490034105404,"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."}}