{"id":"W1523368156","doi":"10.1049/iet-com.2009.0827","title":"Spectral efficiency analysis of rate-adaptive user selection diversity in orthogonal space time block coding multiple-input multiple-output systems with antenna selection","year":2011,"lang":"en","type":"article","venue":"IET Communications","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Montréal; Polytechnique Montréal","funders":"","keywords":"Spectral efficiency; MIMO; Diversity gain; Block code; Computer science; Selection (genetic algorithm); Space–time block code; Algorithm; Coding (social sciences); Mathematics; Control theory (sociology); Telecommunications; Channel (broadcasting); Statistics; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002403847,0.0002053769,0.0003609188,0.0005689028,0.0003045534,0.00001849422,0.0003941034,0.0001076576,0.00001189732],"category_scores_gemma":[0.00004749779,0.0002210112,0.00008266987,0.002753973,0.0001056613,0.0003197949,0.0001524505,0.000322908,0.000006370277],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002750718,"about_ca_system_score_gemma":0.00002933445,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005787691,"about_ca_topic_score_gemma":0.003703597,"domain_scores_codex":[0.9987555,0.0001911164,0.0003676369,0.0002347635,0.0001717844,0.0002791985],"domain_scores_gemma":[0.9986558,0.000306354,0.0001859753,0.0005382798,0.0002517066,0.00006187394],"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":[0.00006567578,0.0001227538,0.1544886,0.0000115745,0.0003031327,5.87019e-7,0.001180495,0.841588,0.001946166,0.0002544688,0.000009985184,0.00002859874],"study_design_scores_gemma":[0.0004424821,0.00006023316,0.09941033,0.00005904926,0.0002460007,0.000003623653,0.0002282416,0.8988267,0.0005035506,0.000004176189,0.000009918776,0.0002057283],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5522492,0.0001226417,0.4462627,0.00001231704,0.00005056914,0.000442524,0.00003072393,0.0002758342,0.0005534685],"genre_scores_gemma":[0.9811574,0.0001644504,0.01845494,0.000002936882,0.00001476602,0.00003465446,0.00007814822,0.00003143732,0.00006124145],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4289083,"threshold_uncertainty_score":0.9012576,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02820450958264754,"score_gpt":0.2204212143652008,"score_spread":0.1922167047825533,"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."}}