{"id":"W1550197964","doi":"10.1109/icc.2015.7248673","title":"Optimum decode-and-forward relay-assisted combining scheme with relay decision information","year":2015,"lang":"en","type":"article","venue":"","topic":"Cooperative Communication and Network Coding","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Relay; Channel state information; Computer science; Maximal-ratio combining; Robustness (evolution); Cooperative diversity; Relay channel; Network packet; Diversity combining; Wireless; Antenna diversity; Channel (broadcasting); Diversity gain; MIMO; Computer network; Telecommunications; Fading","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001382194,0.0009511368,0.001753396,0.0008241357,0.0007002244,0.001093166,0.001263393,0.0009694208,0.0008275909],"category_scores_gemma":[0.001888032,0.0005238149,0.0009818615,0.001673281,0.0008308799,0.001345671,0.001263107,0.0007635018,0.0005284046],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006549699,"about_ca_system_score_gemma":0.0006428932,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005759631,"about_ca_topic_score_gemma":0.0008860222,"domain_scores_codex":[0.9977769,0.0007412468,0.0001617222,0.0003591132,0.0007059361,0.0002550586],"domain_scores_gemma":[0.9990037,0.0003040546,0.0002236161,0.0002103437,0.0002182074,0.0000400761],"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":[0.001783322,0.0002218759,0.003153614,0.0005675572,0.0007349627,0.001617552,0.0009183871,0.4341683,0.1534145,0.09562857,0.004881128,0.3029102],"study_design_scores_gemma":[0.0001180562,0.0005185448,0.0008561809,0.00003708278,0.000395744,0.002078055,0.00005578274,0.9133076,0.0504711,0.02476613,0.007236348,0.0001593111],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03264496,0.001061425,0.9606719,0.0002579361,0.00004851498,0.00005917296,0.0001066525,0.0003531107,0.004796325],"genre_scores_gemma":[0.7531669,0.001278649,0.2422185,0.0001498924,0.0001002585,0.00009276291,0.0001902281,0.00003033956,0.002772449],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001753396,"threshold_uncertainty_score":0.007309794,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04094802524530508,"score_gpt":0.2749784493309792,"score_spread":0.2340304240856741,"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."}}