{"id":"W2000852639","doi":"10.1109/tcomm.2013.032013.120322","title":"Resource Allocation for Selective Relaying Based Cellular Wireless System with Imperfect CSI","year":2013,"lang":"en","type":"article","venue":"IEEE Transactions on Communications","topic":"Cooperative Communication and Network Coding","field":"Computer Science","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Telecommunications link; Karush–Kuhn–Tucker conditions; Probabilistic logic; Resource allocation; Quality of service; Mathematical optimization; Power control; Transmitter power output; Optimization problem; Fading; Channel state information; Channel (broadcasting); Computer network; Wireless; Power (physics); Mathematics; Algorithm; Telecommunications; Transmitter","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":[0.00045946,0.0006085971,0.0006383497,0.0002663118,0.0005070756,0.0006593959,0.0008373357,0.0004786955,0.0005902],"category_scores_gemma":[0.001552018,0.0002289153,0.000285917,0.0003749407,0.0006759752,0.0008085727,0.0007268071,0.0004149258,0.000184394],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006951284,"about_ca_system_score_gemma":0.000611653,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002611099,"about_ca_topic_score_gemma":0.002924547,"domain_scores_codex":[0.9994751,0.0001217632,0.00002982889,0.0001104791,0.0001402719,0.000122685],"domain_scores_gemma":[0.9993943,0.000314406,0.0001165574,0.00006738947,0.00007831336,0.00002905384],"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":[0.0001070457,0.00003745312,0.0007033556,0.00007167176,0.00004172448,0.0003024333,0.0001360975,0.9321172,0.01310392,0.01872924,0.0006252289,0.03402473],"study_design_scores_gemma":[0.000008139554,0.00003144112,0.0001129062,0.000002813818,0.00001186123,0.00005719951,0.00001857889,0.99477,0.001394399,0.003323756,0.0002618323,0.000007053486],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0843723,0.0003719665,0.9121572,0.0001895185,0.00002661943,0.00004525826,0.00004634885,0.0001785791,0.002612266],"genre_scores_gemma":[0.9798903,0.0001513508,0.01921838,0.00003810698,0.00001859571,0.00003784462,0.0000181594,0.000006565906,0.0006207335],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002611099,"threshold_uncertainty_score":0.005191803,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03004630231263103,"score_gpt":0.2506374002990045,"score_spread":0.2205910979863735,"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."}}