{"id":"W3088521885","doi":"10.1186/s13638-020-01798-y","title":"Planning capacity for 5G and beyond wireless networks by discrete fireworks algorithm with ensemble of local search methods","year":2020,"lang":"en","type":"article","venue":"EURASIP Journal on Wireless Communications and Networking","topic":"Cooperative Communication and Network Coding","field":"Computer Science","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"Lakehead University; Simon Fraser University","funders":"","keywords":"Computer science; RSS; Wireless network; Wireless; Local search (optimization); Algorithm; Heuristic; Wi-Fi; Artificial intelligence; 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":[0.001356455,0.0002680295,0.0004670275,0.00008708571,0.00129633,0.0003569093,0.001450695,0.0001122138,0.000001683812],"category_scores_gemma":[0.00001344416,0.0002279954,0.00007630795,0.0005961944,0.0003959196,0.000369086,0.0005442807,0.001089219,2.173219e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004211648,"about_ca_system_score_gemma":0.00005703543,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004067266,"about_ca_topic_score_gemma":0.000006381698,"domain_scores_codex":[0.9975367,0.0009294398,0.0005411768,0.0003566529,0.0002344988,0.0004015052],"domain_scores_gemma":[0.9964675,0.001724203,0.0003653086,0.0008666131,0.0002527586,0.0003235872],"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":[0.0000520617,0.00004571164,0.0003722027,0.00001687571,0.00008453204,0.000002117287,0.001961578,0.004619082,0.0003046033,0.005085542,0.0003050738,0.9871506],"study_design_scores_gemma":[0.0007177648,0.0004330971,0.0001396114,0.0003834509,0.00002433472,0.00006146755,0.0002744423,0.9870681,0.0003710493,0.0001644329,0.01008134,0.0002808735],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.005473836,0.01407171,0.9757112,0.00402922,0.00008768421,0.0002628704,0.000004021374,0.00005051948,0.0003089473],"genre_scores_gemma":[0.8050237,0.01465941,0.1793682,0.0007585999,0.0001246986,0.00002049653,0.00001045181,0.00002641993,0.00000808154],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9868698,"threshold_uncertainty_score":0.997045,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07781382253293476,"score_gpt":0.3397085020916341,"score_spread":0.2618946795586993,"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."}}