{"id":"W2130301039","doi":"10.1109/atc.2008.4760613","title":"A multi-agent protocol to manage interference in a distributed base station system","year":2008,"lang":"en","type":"article","venue":"","topic":"Wireless Communication Networks Research","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"","keywords":"Computer science; Base station; Computer network; Interference (communication); Relay; Protocol (science); Distributed computing; Wireless; Wireless network; Channel (broadcasting); Macro; Scheme (mathematics); Topology (electrical circuits); Engineering; 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":[0.0003885263,0.0001027295,0.0001258129,0.0002119208,0.0000970533,0.0000976343,0.001487811,0.00003477106,0.0000137943],"category_scores_gemma":[0.00005517802,0.00009134742,0.00002412842,0.001078626,0.00002587248,0.0003195033,0.000843712,0.0001629608,0.0001801823],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002808196,"about_ca_system_score_gemma":0.00006228824,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002939348,"about_ca_topic_score_gemma":0.0003407778,"domain_scores_codex":[0.998525,0.0002801716,0.0003091875,0.000325833,0.000275528,0.000284261],"domain_scores_gemma":[0.9985527,0.00009553364,0.00005195299,0.00102681,0.0001324305,0.0001405683],"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":[0.001080064,0.008841498,0.07157261,0.002743419,0.0001879848,0.003190102,0.05278014,0.2308085,0.0148432,0.2271052,0.05315386,0.3336934],"study_design_scores_gemma":[0.0006434253,0.00006088219,0.01711544,0.0001042638,2.662538e-7,0.00001170485,0.0001025659,0.9800274,0.0005134062,0.000008871875,0.001284276,0.0001274607],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.004224124,0.000001904167,0.9656382,0.0005789922,0.00002254794,0.02878829,0.000003793231,0.0002053665,0.0005368234],"genre_scores_gemma":[0.8349008,0.00000101946,0.09754525,0.00007235711,0.000006406925,0.06714282,0.0000067543,0.000006030784,0.0003185764],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8680929,"threshold_uncertainty_score":0.372504,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08215795772936059,"score_gpt":0.3395224476944072,"score_spread":0.2573644899650466,"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."}}