{"id":"W4360996555","doi":"10.1109/icct56141.2022.10073456","title":"IDSM: Intent-Driven Slice Management and Maintenance for 6G RANs","year":2022,"lang":"en","type":"article","venue":"","topic":"Software-Defined Networks and 5G","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"National Natural Science Foundation of China","keywords":"Computer science; Computer network; Network management station; Network management; Software-defined networking; Application lifecycle management; Wireless network; Key (lock); Abstraction; Network element; Network architecture; Distributed computing; Wireless; Software; Telecommunications; Operating system","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":[0.001221666,0.0007660657,0.0004295828,0.0009854533,0.0006721693,0.001203015,0.001970418,0.0006429575,0.001448968],"category_scores_gemma":[0.002094191,0.0003228881,0.000479934,0.0003681384,0.000763687,0.002056584,0.002840118,0.001041207,0.0006329794],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007374992,"about_ca_system_score_gemma":0.001108289,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002799308,"about_ca_topic_score_gemma":0.002609791,"domain_scores_codex":[0.9989842,0.0001291596,0.00009518872,0.0001775675,0.0004738964,0.0001401084],"domain_scores_gemma":[0.9989957,0.00008899073,0.0001702944,0.0003581944,0.0002873634,0.00009945581],"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":[0.0004897949,0.0003158637,0.01055887,0.0003687475,0.00009930794,0.001151147,0.00174623,0.06024299,0.1244969,0.0614862,0.02013098,0.718913],"study_design_scores_gemma":[0.00005808922,0.0004109843,0.003594459,0.0001324373,0.0001010373,0.0009232796,0.0003994746,0.8308401,0.09052799,0.01916129,0.05372928,0.0001215663],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01852698,0.000404318,0.9687638,0.0001907962,0.0001175789,0.0002738157,0.0001263513,0.007741459,0.003854949],"genre_scores_gemma":[0.4804733,0.0003391629,0.5139494,0.0002826942,0.00008141081,0.0002131933,0.0007700206,0.0003209721,0.003569952],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002799308,"threshold_uncertainty_score":0.006460905,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01255251696995068,"score_gpt":0.2135980538263079,"score_spread":0.2010455368563572,"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."}}