{"id":"W2102105576","doi":"10.1109/tcomm.2009.03.070115","title":"Optimal adaptive modulation and coding with switching costs","year":2009,"lang":"en","type":"article","venue":"IEEE Transactions on Communications","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Link adaptation; Fading; Coding (social sciences); Computer science; Markov decision process; Adaptive coding; Mathematical optimization; Monotonic function; Markov process; Control theory (sociology); Channel (broadcasting); Mathematics; Algorithm; Telecommunications","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":[0.0007888295,0.0006389052,0.0006364547,0.0004240442,0.0003023005,0.0009013072,0.0008983694,0.0007487829,0.001912852],"category_scores_gemma":[0.004125218,0.0002552236,0.0002729568,0.0006025227,0.0008360768,0.001246217,0.000754255,0.0009588832,0.0001751654],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001169614,"about_ca_system_score_gemma":0.001683042,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002830026,"about_ca_topic_score_gemma":0.001883983,"domain_scores_codex":[0.9993014,0.0002126095,0.00002909403,0.0001032028,0.000201926,0.0001517297],"domain_scores_gemma":[0.9984418,0.001046224,0.0001718128,0.00009290236,0.0001827069,0.0000646064],"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":[0.0001218746,0.00006618637,0.0003457032,0.00005472474,0.00001809783,0.00009404343,0.00004024695,0.893451,0.003707093,0.06804072,0.0007698348,0.03329045],"study_design_scores_gemma":[0.00001618028,0.00002441418,0.00006459279,0.000005319532,0.000005287794,0.00001931281,0.000007211095,0.9843762,0.0008854823,0.01434444,0.0002459011,0.000005749176],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07821638,0.0004892506,0.9126275,0.0005454437,0.00006392089,0.00009231966,0.00009149995,0.0001370444,0.007736664],"genre_scores_gemma":[0.9391936,0.0002217173,0.05844761,0.00008799159,0.00003617413,0.00008955789,0.00004407931,0.00002167782,0.001857497],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002830026,"threshold_uncertainty_score":0.008486152,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01572887581231406,"score_gpt":0.2349769047716076,"score_spread":0.2192480289592936,"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."}}