{"id":"W4386057507","doi":"10.1109/isit54713.2023.10206990","title":"Distributed Lossy Computation with Structured Codes: From Discrete to Continuous Sources","year":2023,"lang":"en","type":"article","venue":"","topic":"Wireless Communication Security Techniques","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia, Okanagan Campus; University of British Columbia","funders":"Ministry of Education; National Research Foundation; National Science Foundation","keywords":"Lossy compression; Decoding methods; Computer science; Encoding (memory); Algorithm; Rate–distortion theory; Encoder; Theoretical computer science; Gaussian; Computation; Data compression; Mathematical optimization; Mathematics; Artificial intelligence","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":[0.00005310237,0.0001299218,0.0001739558,0.00008654209,0.00005356845,0.00008052099,0.0002365737,0.00005727897,0.00003853482],"category_scores_gemma":[0.00001418558,0.0001120986,0.00002227449,0.0004278292,0.00002997722,0.00008745202,0.00006944319,0.0001098482,0.00006567052],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003656456,"about_ca_system_score_gemma":0.000006299858,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001894643,"about_ca_topic_score_gemma":0.0003512573,"domain_scores_codex":[0.999348,0.00002561132,0.000168133,0.0001387764,0.0001538791,0.0001655428],"domain_scores_gemma":[0.9994361,0.000100855,0.00002396636,0.0003135274,0.00005327105,0.00007223943],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001859245,0.00006805242,0.02743559,0.0001892183,0.0007820937,0.00005429572,0.01633206,0.7298759,0.06141436,0.007753798,0.1117732,0.04413555],"study_design_scores_gemma":[0.001430856,0.0002199086,0.1309163,0.0002825593,0.00006941632,0.000007824662,0.003538454,0.6917656,0.129733,0.007554961,0.03290714,0.001574056],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.658431,0.00002566235,0.3367919,0.0002706775,0.00002990636,0.0002079298,0.000234108,0.003489148,0.0005196658],"genre_scores_gemma":[0.9844633,0.00001377005,0.0143853,0.00004652171,0.00002136835,0.00003603645,0.0009688163,0.00003284658,0.00003202362],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3260323,"threshold_uncertainty_score":0.4571247,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009160112584267278,"score_gpt":0.2407645468340261,"score_spread":0.2316044342497589,"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."}}