{"id":"W2035061388","doi":"10.1504/ijaacs.2014.058013","title":"A local search heuristic to solve the planning problem of 3G UMTS all-IP release 4 networks with realistic traffic","year":2013,"lang":"en","type":"article","venue":"International Journal of Autonomous and Adaptive Communications Systems","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Computer science; UMTS frequency bands; Heuristic; Local search (optimization); Mathematical optimization; Incremental heuristic search; Network planning and design; Search algorithm; Algorithm; Computer network; Beam search; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003351329,0.0001379553,0.0002517883,0.0001485026,0.00008878401,0.00009732282,0.0007385911,0.00004674526,0.000005043635],"category_scores_gemma":[0.00002158359,0.00009816391,0.00004466122,0.0001580103,0.0001465051,0.0002024342,0.000104715,0.0003281586,0.000002831993],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001660999,"about_ca_system_score_gemma":0.00005853813,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008738734,"about_ca_topic_score_gemma":0.00001980495,"domain_scores_codex":[0.998697,0.00009997895,0.0006605352,0.00009490889,0.0002924625,0.0001550728],"domain_scores_gemma":[0.9979777,0.0004249307,0.000310086,0.0003468333,0.0008377167,0.0001027335],"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":[0.00003768189,0.00003280688,0.00005275513,0.00001273163,0.0002150866,0.000004913034,0.0008650008,0.9877585,0.00003434047,0.002292538,0.0003686568,0.008325008],"study_design_scores_gemma":[0.0002901449,0.0001529803,0.0007464084,0.0005147769,0.00002940249,0.0001543611,0.001246604,0.9957457,0.000007240462,0.0000470063,0.0009576199,0.0001077598],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02095222,0.002279235,0.9751652,0.0005304603,0.0001436225,0.000417555,0.0000129076,0.00002855292,0.0004701844],"genre_scores_gemma":[0.976615,0.0003360574,0.02281314,0.0000308137,0.00009650939,0.00003936517,0.00001448331,0.00002710658,0.0000275067],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9556628,"threshold_uncertainty_score":0.4003008,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02260417451414537,"score_gpt":0.2580560771798455,"score_spread":0.2354519026657001,"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."}}