{"id":"W2171848435","doi":"10.1109/glocom.2010.5683386","title":"Estimation, Training, and Effect of Timing Offsets in Distributed Cooperative Networks","year":2010,"lang":"en","type":"article","venue":"","topic":"Cooperative Communication and Network Coding","field":"Computer Science","cited_by":25,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Estimator; Computer science; Relay; Cramér–Rao bound; Synchronization (alternating current); Upper and lower bounds; Algorithm; Sequence (biology); Computational complexity theory; Interference (communication); Offset (computer science); Estimation; Real-time computing; Estimation theory; Channel (broadcasting); Telecommunications; Statistics; Mathematics; Engineering","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":[0.0005123871,0.00008582816,0.000162469,0.0000594231,0.00008285211,0.00005573868,0.0003017906,0.00004489657,0.00002332355],"category_scores_gemma":[0.000172579,0.00006906894,0.00001566454,0.0003758709,0.00006420389,0.0002351935,0.0001729361,0.0002067566,0.000001372664],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000007642933,"about_ca_system_score_gemma":0.00002356883,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006820694,"about_ca_topic_score_gemma":0.0001748678,"domain_scores_codex":[0.9993328,0.0001315283,0.0001908187,0.0001571549,0.00006852148,0.000119187],"domain_scores_gemma":[0.9991663,0.0003872025,0.00005379035,0.000286162,0.00006123939,0.00004529997],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001576461,0.00006329595,0.01531518,0.00001546238,0.00002027157,0.000003568604,0.003437095,0.01258948,0.00305901,0.1911392,0.0006408461,0.7737008],"study_design_scores_gemma":[0.0003667277,0.00006784482,0.01076147,0.00002365026,0.000001667919,0.000004671033,0.00001073948,0.9870694,0.001355823,0.00006180619,0.0001972859,0.00007889586],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2548173,0.00008281231,0.7434516,0.0004040549,0.00009578341,0.0001640036,8.251559e-7,0.00004938571,0.0009342132],"genre_scores_gemma":[0.9915285,0.00004507248,0.008312038,0.00005678967,0.000009760216,0.00001177206,0.000008778517,0.000002967789,0.00002438616],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9744799,"threshold_uncertainty_score":0.281655,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02378310513926922,"score_gpt":0.2897666608812662,"score_spread":0.2659835557419969,"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."}}