{"id":"W4396752925","doi":"10.2139/ssrn.4820782","title":"Automated Orchestration of Virtualized Mobile Core Network Deployments","year":2024,"lang":"en","type":"preprint","venue":"SSRN Electronic Journal","topic":"Telecommunications and Broadcasting Technologies","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Regina","funders":"","keywords":"Orchestration; Computer science; Core (optical fiber); Network Functions Virtualization; Core network; Operating system; Computer network; Cloud computing; 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":["research_integrity"],"consensus_categories":[],"category_scores_codex":[0.0007793429,0.0002570796,0.0003412726,0.0001913334,0.00008090727,0.00007139995,0.0006733458,0.0003598993,0.00001021133],"category_scores_gemma":[0.00003585309,0.0002434423,0.0001570729,0.0002836892,0.00005205095,0.00004163439,0.0004145055,0.00457097,0.00001540772],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008051114,"about_ca_system_score_gemma":0.0008538396,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002411243,"about_ca_topic_score_gemma":0.000130133,"domain_scores_codex":[0.9979167,0.00004031748,0.0005538578,0.0001748913,0.0001820902,0.001132135],"domain_scores_gemma":[0.9991498,0.00005031421,0.0001897868,0.0005011923,0.00007690871,0.0000320277],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00002666759,0.00008649434,0.0002843338,0.0003721357,0.001617296,0.000006671362,0.000247979,0.8623224,0.002751198,0.04019127,0.003940926,0.08815258],"study_design_scores_gemma":[0.0003658958,0.0002663696,0.0001018325,0.0007149143,0.0002185063,0.0002144106,0.0005672303,0.3488312,0.0007696791,0.646186,0.001280164,0.0004838212],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9371977,0.04600612,0.009176013,0.0000894986,0.001027856,0.0004821265,0.00002289256,0.005227511,0.0007703107],"genre_scores_gemma":[0.9805134,0.0164156,0.002640096,0.00000289079,0.0001393116,0.00006208597,0.00004063003,0.00007390261,0.0001121022],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6059947,"threshold_uncertainty_score":0.9977255,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01814044742703237,"score_gpt":0.2742298080908022,"score_spread":0.2560893606637699,"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."}}