{"id":"W2141560854","doi":"10.1002/wcm.1150","title":"Antenna subset selection at multi‐antenna relay with adaptive modulation","year":2011,"lang":"en","type":"article","venue":"Wireless Communications and Mobile Computing","topic":"Cooperative Communication and Network Coding","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"Wonkwang University","keywords":"Computer science; Relay; Antenna (radio); Spectral efficiency; Transmission (telecommunications); Link adaptation; Selection (genetic algorithm); Telecommunications; Hop (telecommunications); Computer network; Diversity gain; Antenna diversity; Electronic engineering; Fading; Decoding methods; Artificial intelligence","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":[0.0006452967,0.0004287094,0.0004444553,0.0003177156,0.000271347,0.0004267242,0.0005933107,0.0003444423,0.0004975003],"category_scores_gemma":[0.001801163,0.0001550316,0.000317277,0.0003752919,0.0003229133,0.0005125131,0.0005012476,0.0003253118,0.0002498454],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002272909,"about_ca_system_score_gemma":0.0001689699,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002082112,"about_ca_topic_score_gemma":0.00025874,"domain_scores_codex":[0.9994684,0.0002903744,0.00002924827,0.0000752946,0.00009211783,0.00004461917],"domain_scores_gemma":[0.9988214,0.0005372994,0.0001259888,0.0002912745,0.0001778187,0.00004623251],"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":[0.001100892,0.0001721714,0.006862986,0.0001915957,0.0002965021,0.0007988609,0.0005478965,0.3480768,0.2445556,0.02789602,0.001989553,0.3675111],"study_design_scores_gemma":[0.00005894195,0.0004436692,0.001311593,0.00001493157,0.00007127109,0.000549954,0.00004695732,0.9466646,0.04193589,0.006480661,0.002394129,0.00002738641],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2433414,0.0008286449,0.752713,0.0001887817,0.00006306232,0.00005195792,0.0000341352,0.0002425145,0.0025366],"genre_scores_gemma":[0.9548184,0.0001551748,0.04425464,0.00004237477,0.00002849996,0.00002627108,0.00002033433,0.000006135733,0.0006481896],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0006452967,"threshold_uncertainty_score":0.003412664,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06785384826491203,"score_gpt":0.2741186257291299,"score_spread":0.2062647774642179,"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."}}