{"id":"W2086285386","doi":"10.1109/tsp.2014.2305643","title":"Scalable and Efficient Power Control Algorithms for Wireless Networks","year":2014,"lang":"en","type":"article","venue":"IEEE Transactions on Signal Processing","topic":"Cooperative Communication and Network Coding","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Power control; Computer science; Algorithm; Initialization; Computational complexity theory; Wireless network; Mathematical optimization; Power optimization; Scalability; Wireless; Power (physics); Mathematics; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004362546,0.0001431101,0.0001655503,0.00008554199,0.0007310151,0.0002763744,0.0003265197,0.00006072911,0.00001040043],"category_scores_gemma":[0.000002796332,0.0001315408,0.00005359163,0.000287983,0.00006598149,0.0002160284,0.000003787308,0.000194483,0.000003660116],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002967165,"about_ca_system_score_gemma":0.00003754394,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":8.640791e-7,"about_ca_topic_score_gemma":0.000002667771,"domain_scores_codex":[0.9989914,0.00009084027,0.000201547,0.0003187563,0.0001434803,0.0002539299],"domain_scores_gemma":[0.9991481,0.0002779807,0.00006835377,0.0002395585,0.0001674467,0.00009858044],"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":[0.00002278121,0.00008702473,0.000002461231,0.00001242004,0.00001160418,2.438184e-7,0.0003235404,0.1569367,0.0008256414,0.0007149116,0.00003203116,0.8410307],"study_design_scores_gemma":[0.0007624839,0.0001169891,0.00002094737,0.00007705289,0.00001095771,0.000005225735,0.00001583057,0.996175,0.00180036,0.00008629081,0.0007646798,0.0001641652],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.001355851,0.0003068074,0.9970999,0.0004897289,0.0001549189,0.0002343047,0.000001457071,0.0001366712,0.0002203234],"genre_scores_gemma":[0.9892281,0.00003109335,0.009949833,0.0006077458,0.00004025795,0.00004441862,4.209176e-7,0.00001331923,0.00008484706],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9878722,"threshold_uncertainty_score":0.5622451,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02194350106647361,"score_gpt":0.2633968238221888,"score_spread":0.2414533227557152,"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."}}