{"id":"W2144295065","doi":"10.1109/jsac.2012.120919","title":"Two-Way Amplify-and-Forward Multiple-Input Multiple-Output Relay Networks with Antenna Selection","year":2012,"lang":"en","type":"article","venue":"IEEE Journal on Selected Areas in Communications","topic":"Cooperative Communication and Network Coding","field":"Computer Science","cited_by":97,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Relay; Computer science; Fading; Diversity gain; Antenna (radio); Cooperative diversity; Relay channel; MIMO; Selection (genetic algorithm); Computer network; Channel state information; Telecommunications; Channel (broadcasting); Topology (electrical circuits); Wireless; Electrical engineering; Engineering; Artificial intelligence; Power (physics)","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":["metaepi_narrow","sts"],"consensus_categories":[],"category_scores_codex":[0.001278493,0.0003443788,0.0003752956,0.0004962957,0.001352379,0.0003811172,0.002223939,0.0001518173,0.000009866578],"category_scores_gemma":[0.0004203063,0.0002950853,0.00007470803,0.002193829,0.0001695062,0.001112798,0.0004377076,0.002235599,0.00002112909],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000326071,"about_ca_system_score_gemma":0.0001506221,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002803818,"about_ca_topic_score_gemma":0.001105091,"domain_scores_codex":[0.9965955,0.001316946,0.0006884536,0.0003283879,0.0003663453,0.0007043597],"domain_scores_gemma":[0.9948015,0.001918199,0.0004292407,0.001796691,0.0006708993,0.0003835087],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005301316,0.003521231,0.7178261,0.00002263204,0.0005959135,0.00001890153,0.0094299,0.05874224,0.005943024,0.03771482,0.003732573,0.1619226],"study_design_scores_gemma":[0.002601051,0.0002939237,0.1266113,0.0003728048,0.00003565544,0.0007895074,0.0001136112,0.8569123,0.0002275202,0.00008171466,0.01131626,0.0006443221],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.126501,0.004768744,0.8601856,0.00468816,0.0006243921,0.0007495155,0.000004726272,0.0004505625,0.002027324],"genre_scores_gemma":[0.9504992,0.005300302,0.04317398,0.0005750376,0.0002239995,0.00006912285,0.00001569509,0.00003716182,0.0001055071],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8239982,"threshold_uncertainty_score":0.9999501,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04527269415622559,"score_gpt":0.2971968397457743,"score_spread":0.2519241455895487,"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."}}