{"id":"W2021924106","doi":"10.1049/iet-com.2012.0596","title":"Performance analysis of adaptive <i>M</i> ‐ary quadrature amplitude modulation for amplify‐and‐forward opportunistic relaying under outdated channel state information","year":2013,"lang":"en","type":"article","venue":"IET Communications","topic":"Cooperative Communication and Network Coding","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Channel state information; Quadrature (astronomy); Adaptive quadrature; Channel (broadcasting); Computer science; Amplitude; Amplitude modulation; Quadrature amplitude modulation; Modulation (music); Telecommunications; Electronic engineering; Control theory (sociology); Physics; Wireless; Frequency modulation; Bandwidth (computing); Acoustics; Engineering; Bit error rate; Artificial intelligence; Optics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0004502755,0.0001597684,0.0002816144,0.0003838324,0.0005571733,0.0001906403,0.001338878,0.00007947602,0.00001136876],"category_scores_gemma":[0.000089788,0.0001583482,0.00008896123,0.001257917,0.0001261056,0.00183763,0.0006850691,0.0002357201,0.00001072219],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006172165,"about_ca_system_score_gemma":0.00008664779,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000054246,"about_ca_topic_score_gemma":0.00007510823,"domain_scores_codex":[0.9986925,0.0001774895,0.0005681366,0.0001847777,0.0001734654,0.0002036341],"domain_scores_gemma":[0.9963166,0.0004676377,0.0003931363,0.001965589,0.0007432449,0.000113846],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000073822,0.0004825165,0.003457489,0.0001423749,0.00240297,1.383594e-7,0.02455247,0.1223039,0.003581229,0.5495235,0.003251444,0.2902281],"study_design_scores_gemma":[0.0002370607,0.00005090628,0.02889332,0.00003297104,0.00009739118,7.91142e-7,0.0002340306,0.9671997,0.0000269062,0.001687348,0.001363551,0.0001760148],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01853809,0.0002858958,0.9761124,0.002916713,0.00006124839,0.0007644093,0.00006968001,0.0001363251,0.001115207],"genre_scores_gemma":[0.9635679,0.001842202,0.0330467,0.0005689601,0.000005980503,0.0002503455,0.0006470022,0.000008258118,0.00006269589],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9450297,"threshold_uncertainty_score":0.6457254,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06497505384593932,"score_gpt":0.2883537230713588,"score_spread":0.2233786692254195,"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."}}