{"id":"W2097812145","doi":"10.1109/lcomm.2002.805515","title":"A memetic algorithm for assigning cells to switches in cellular mobile networks","year":2002,"lang":"en","type":"article","venue":"IEEE Communications Letters","topic":"Wireless Communication Networks Research","field":"Computer Science","cited_by":38,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Memetic algorithm; Tabu search; Computer science; Heuristics; Cellular network; Heuristic; Context (archaeology); Memetics; Algorithm; Local search (optimization); Mathematical optimization; Artificial intelligence; Mathematics; Computer network","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":["open_science"],"consensus_categories":[],"category_scores_codex":[0.0009260216,0.0002091789,0.0002687444,0.0004278875,0.0004206838,0.0002937971,0.007261476,0.00009643148,0.00001473519],"category_scores_gemma":[0.00003589594,0.000236469,0.0001097701,0.001576646,0.0001370942,0.0003974898,0.001186572,0.0005531884,0.0001048515],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002035094,"about_ca_system_score_gemma":0.00002464893,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005485178,"about_ca_topic_score_gemma":0.00004930177,"domain_scores_codex":[0.9976938,0.0004351256,0.0005106222,0.0004371642,0.0003071251,0.0006162121],"domain_scores_gemma":[0.992942,0.001285097,0.0001251471,0.005332808,0.0001379045,0.0001770673],"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":[0.000004405324,0.0006425164,0.0001439187,0.00002118043,0.00006423052,0.000006461968,0.003428263,0.2884715,0.0710976,0.001183914,0.04674171,0.5881943],"study_design_scores_gemma":[0.0003359183,0.000044738,0.00003966171,0.00005174223,0.000004631917,0.000001845745,0.00004954876,0.9727579,0.003653067,0.00005186378,0.02274358,0.0002655453],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.003335328,0.00130773,0.97994,0.01359898,0.0002020185,0.001164664,0.000003661532,0.0001716129,0.0002759855],"genre_scores_gemma":[0.5881237,0.0004365148,0.407177,0.002228581,0.00006643025,0.001790839,0.00001031652,0.00003367266,0.0001328538],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.6842863,"threshold_uncertainty_score":0.9981097,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05095501752109461,"score_gpt":0.2887896770371899,"score_spread":0.2378346595160953,"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."}}