{"id":"W2290409208","doi":"10.1109/acssc.2015.7421353","title":"A coordinated uplink scheduling and power control algorithm for multicell networks","year":2015,"lang":"en","type":"article","venue":"","topic":"Advanced MIMO Systems Optimization","field":"Engineering","cited_by":26,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Telecommunications link; Computer science; Power control; Scheduling (production processes); Mathematical optimization; Transmitter power output; Integer programming; Maximization; Algorithm; Distributed computing; Computer network; Power (physics); Mathematics; Channel (broadcasting)","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":[0.0004864321,0.0006468118,0.0006828477,0.0003000328,0.0005133095,0.0007047031,0.0009733786,0.0006906991,0.001413193],"category_scores_gemma":[0.001096009,0.0002951059,0.0003548954,0.0005113318,0.0004319983,0.0005942301,0.0007956359,0.0009462697,0.0004015693],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008135247,"about_ca_system_score_gemma":0.00117024,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00449904,"about_ca_topic_score_gemma":0.004010973,"domain_scores_codex":[0.9995073,0.0001099876,0.00001615809,0.0001125713,0.0001806049,0.00007329719],"domain_scores_gemma":[0.999691,0.0001193138,0.00004870385,0.00003129759,0.00008452978,0.0000251686],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00006852238,0.00006629337,0.0002385629,0.00004341497,0.00003012583,0.00005144011,0.00007095507,0.8383618,0.005053666,0.01490402,0.002250772,0.1388604],"study_design_scores_gemma":[0.0000090668,0.00002403509,0.00003461763,0.000002182604,0.000003388407,0.00001109251,0.00000534118,0.9971795,0.0006222461,0.001410169,0.0006955222,0.000002956969],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.003933298,0.0001006473,0.9941348,0.00005447138,0.0000220483,0.00001809309,0.00001195243,0.0001759138,0.001548788],"genre_scores_gemma":[0.5151697,0.000275926,0.4790883,0.000135701,0.00009101184,0.000258298,0.0001081863,0.0001037022,0.004769205],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.00449904,"threshold_uncertainty_score":0.008945704,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009444419152925444,"score_gpt":0.2233969054690531,"score_spread":0.2139524863161277,"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."}}