{"id":"W1497819923","doi":"10.1109/icc.2015.7248629","title":"Complex Low Density Lattice Codes to Physical Layer Network Coding","year":2015,"lang":"en","type":"article","venue":"","topic":"Cooperative Communication and Network Coding","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Engineering and Physical Sciences Research Council; University of Toronto","keywords":"Linear network coding; Computer science; Coding gain; Coding (social sciences); Lattice (music); Decoding methods; Shannon–Fano coding; Variable-length code; Parametric statistics; Relay; Channel code; Algorithm; Topology (electrical circuits); Theoretical computer science; Mathematics; Computer network; Physics; Combinatorics","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000425195,0.0001210059,0.0001835802,0.00003329498,0.0002190815,0.0002027748,0.0009196885,0.00002478556,0.00002204242],"category_scores_gemma":[0.00007318636,0.0001069287,0.00004147637,0.0005589998,0.0000338943,0.0002544764,0.0009586411,0.0001301123,0.0004010975],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005523597,"about_ca_system_score_gemma":0.00004905566,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009562242,"about_ca_topic_score_gemma":0.00009973512,"domain_scores_codex":[0.9989077,0.0001738697,0.0001416195,0.0002695751,0.0002216879,0.0002855632],"domain_scores_gemma":[0.9985531,0.0001938881,0.00003572057,0.0006964187,0.0002525999,0.0002682934],"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":[0.00001539167,0.0001169363,0.002153222,0.000004618355,0.00002573325,0.00000753516,0.002638031,0.005811988,0.002082529,0.8173686,0.1387602,0.03101521],"study_design_scores_gemma":[0.0004239422,0.00009284142,0.009087237,0.00003797357,0.000006341816,0.000009630228,0.00005741863,0.937775,0.00148733,0.003542247,0.04709031,0.0003897298],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06825931,0.00004665437,0.9019606,0.004971202,0.0002411802,0.0001751931,4.223913e-7,0.0003361563,0.02400933],"genre_scores_gemma":[0.93108,0.00001195442,0.06399377,0.004121427,0.0002258678,0.000006918017,0.000002122324,0.000006396075,0.0005515078],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.931963,"threshold_uncertainty_score":0.5155431,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1361905671106673,"score_gpt":0.3342500014932132,"score_spread":0.1980594343825459,"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."}}