{"id":"W2742585922","doi":"10.1109/isit.2017.8006843","title":"Towards an algebraic network information theory: Simultaneous joint typicality decoding","year":2017,"lang":"en","type":"article","venue":"","topic":"Cooperative Communication and Network Coding","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Decoding methods; Code word; Tuple; Computer science; Theoretical computer science; Linear code; Code (set theory); Encoder; Encoding (memory); Random access; Coding (social sciences); Algorithm; Mathematics; Block code; Discrete 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":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.001113083,0.0001206862,0.0001445166,0.00003615603,0.001266723,0.001211018,0.001805769,0.00005630732,0.0001313323],"category_scores_gemma":[0.0005594841,0.0001010785,0.00004930333,0.0001043621,0.00007045765,0.00249632,0.000919885,0.0001640113,0.0001293449],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004368994,"about_ca_system_score_gemma":0.00006113108,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001152466,"about_ca_topic_score_gemma":0.00006703479,"domain_scores_codex":[0.9989214,0.0002096273,0.0002673939,0.0001802534,0.0001682977,0.0002530212],"domain_scores_gemma":[0.9975476,0.000135446,0.0001777459,0.001834162,0.0001767363,0.0001282676],"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":[0.000004159665,0.00001106797,0.0001054072,0.000001585286,0.000005389728,8.246163e-7,0.000346395,0.0005510653,0.00001422038,0.5794219,0.0003165938,0.4192214],"study_design_scores_gemma":[0.0003071685,0.0000693042,0.01037811,0.00002671418,0.000004671943,0.000008022294,0.00003702077,0.9120021,0.0002799983,0.05407418,0.02252334,0.0002893345],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.007889004,0.00005981805,0.9425102,0.001991258,0.0003420036,0.00014813,5.697613e-7,0.0002675513,0.04679143],"genre_scores_gemma":[0.9576137,0.0001139241,0.04043545,0.001534372,0.0001064703,0.00000775989,0.000005361236,0.000004108461,0.0001788356],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9497247,"threshold_uncertainty_score":0.9998258,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04909971794798162,"score_gpt":0.3034937500324671,"score_spread":0.2543940320844855,"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."}}