{"id":"W4287725352","doi":"10.48550/arxiv.2007.05370","title":"Design and Practical Decoding of Full-Diversity Construction A Lattices\\n for Block-Fading Channels","year":2020,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Cooperative Communication and Network Coding","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Low-density parity-check code; Fading; Decoding methods; Lattice (music); List decoding; Algorithm; Computer science; Binary number; Algebraic structure; Mathematics; Block code; Theoretical computer science; Topology (electrical circuits); Concatenated error correction code; Arithmetic; Combinatorics; Pure mathematics; Physics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0004518099,0.0004239486,0.0003321787,0.0003212913,0.0003965331,0.000712089,0.0005096362,0.0004819533,0.001018131],"category_scores_gemma":[0.001873768,0.0002463239,0.000391228,0.0003574165,0.0009261863,0.0006025899,0.001098516,0.0007330714,0.0003479979],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006204829,"about_ca_system_score_gemma":0.001043148,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005830784,"about_ca_topic_score_gemma":0.0007366191,"domain_scores_codex":[0.9993524,0.0002177517,0.00004244675,0.00009342085,0.0002228308,0.00007127344],"domain_scores_gemma":[0.9991024,0.0003581114,0.0001377748,0.0001977132,0.0001426863,0.00006140397],"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":[0.0002390061,0.0001036617,0.001337068,0.0002712901,0.00003709344,0.0002677301,0.0003435099,0.3072369,0.08367256,0.4480149,0.002444779,0.1560315],"study_design_scores_gemma":[0.00005486042,0.0001738259,0.0002279025,0.00002910316,0.000009672863,0.0002382778,0.00005075114,0.8912203,0.04617845,0.05630603,0.005469579,0.00004119827],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04737517,0.000126315,0.9466461,0.0001245349,0.00003330019,0.00005248086,0.00009252479,0.0002736981,0.005275863],"genre_scores_gemma":[0.5648298,0.0002358995,0.43158,0.00007998464,0.00002942701,0.0001470719,0.0001954366,0.00005595529,0.002846528],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001018131,"threshold_uncertainty_score":0.004501939,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2421524679573243,"score_gpt":0.2574673768636078,"score_spread":0.01531490890628345,"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."}}