{"id":"W2135183970","doi":"10.1109/tsmcb.2003.817073","title":"A two-phase genetic K-means algorithm for placement of radioports in cellular networks","year":2004,"lang":"en","type":"article","venue":"IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)","topic":"Wireless Communication Networks Research","field":"Computer Science","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Simplex algorithm; Algorithm; Genetic algorithm; Computation; Computer science; Simplex; Range (aeronautics); Channel (broadcasting); Phase (matter); Wireless; Mathematical optimization; Mathematics; Linear programming; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007890122,0.0008994897,0.001039107,0.0008882475,0.0008319755,0.0006855623,0.001314549,0.001444917,0.001335514],"category_scores_gemma":[0.002102895,0.0006843083,0.0006390939,0.0008830732,0.0008851371,0.0007843404,0.0009206732,0.0007713737,0.0004347262],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008096872,"about_ca_system_score_gemma":0.001654731,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007835344,"about_ca_topic_score_gemma":0.007550428,"domain_scores_codex":[0.9994866,0.0001945474,0.00002390144,0.00009238996,0.0001563806,0.00004618095],"domain_scores_gemma":[0.9994062,0.0003391353,0.00006187175,0.00004264396,0.0001221814,0.00002796174],"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":[0.00007398802,0.00005842711,0.000380829,0.00005038307,0.00004952832,0.00003618914,0.000094043,0.8732607,0.002249625,0.005136906,0.001116997,0.1174924],"study_design_scores_gemma":[0.00002568579,0.00003430007,0.00005434603,0.000003751067,0.000006398427,0.00001816242,0.00001126606,0.9966801,0.0006105372,0.002038135,0.0005088968,0.00000835408],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.006409661,0.00006783983,0.992498,0.00005185932,0.00001812451,0.00003849842,0.0000103402,0.0002638863,0.0006419176],"genre_scores_gemma":[0.163429,0.0001079045,0.8342515,0.00009563607,0.00002680951,0.0003598653,0.00007787981,0.00007922379,0.001572175],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007835344,"threshold_uncertainty_score":0.01557952,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02327623352327036,"score_gpt":0.2791035902247651,"score_spread":0.2558273567014947,"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."}}