{"id":"W2152339012","doi":"10.1109/lcomm.2006.1638613","title":"Global expansion model for mobile networks","year":2006,"lang":"en","type":"article","venue":"IEEE Communications Letters","topic":"Advanced MIMO Systems Optimization","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"UMTS frequency bands; Computer science; Core network; Cellular network; Generalization; Mathematical optimization; Network planning and design; Mobile telephony; Computer network; Network model; Distributed computing; Core (optical fiber); Telecommunications; Mobile radio; Artificial intelligence; Mathematics","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":[0.0005819078,0.0009024006,0.0007580685,0.0004353964,0.0003412348,0.0009841021,0.001163697,0.0009799537,0.007129687],"category_scores_gemma":[0.001119991,0.0003210026,0.00058585,0.0005321966,0.0008225992,0.002392687,0.001062153,0.001352508,0.000706062],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009330182,"about_ca_system_score_gemma":0.0006077517,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003115288,"about_ca_topic_score_gemma":0.002855289,"domain_scores_codex":[0.9997009,0.00009610745,0.000006187864,0.00006300314,0.00007557515,0.00005828778],"domain_scores_gemma":[0.9996859,0.0001603614,0.00003588686,0.00002261017,0.00006667025,0.00002872436],"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":[0.00001960315,0.00001189396,0.0001329825,0.00003385542,0.00001108894,0.0000906944,0.00004269372,0.847416,0.0007263656,0.1433363,0.001984065,0.006194461],"study_design_scores_gemma":[0.000005302794,0.00001298219,0.00003806145,0.000004585808,0.000003963217,0.0000220833,0.00001336682,0.9736442,0.00009853108,0.02423247,0.001920576,0.000003848432],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01798304,0.0006034986,0.9594835,0.0004736707,0.00006174576,0.00003194765,0.0001279363,0.0001649339,0.02106963],"genre_scores_gemma":[0.8714581,0.001857552,0.08039462,0.0004204774,0.0001726037,0.0003282545,0.0004391395,0.0002398548,0.04468948],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007129687,"threshold_uncertainty_score":0.02385122,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01542579294915918,"score_gpt":0.2512800604742272,"score_spread":0.235854267525068,"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."}}