{"id":"W4413920164","doi":"10.1016/j.comnet.2025.111657","title":"DETROIT: Decomposition techniques for a hierarchy of 6G network intent management functions","year":2025,"lang":"en","type":"article","venue":"Computer Networks","topic":"Software-Defined Networks and 5G","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"H2020 Excellent Science; Türkiye Bilimsel ve Teknolojik Araştırma Kurumu; European Commission","keywords":"Computer science; Decomposition; Hierarchy; Network management; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009424328,0.0009924528,0.0004972699,0.001536171,0.0009292548,0.001488208,0.001014475,0.0004610645,0.01097038],"category_scores_gemma":[0.001758703,0.0004422067,0.0009250204,0.0008757848,0.0004006922,0.001615611,0.001802248,0.001574037,0.002941474],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007772915,"about_ca_system_score_gemma":0.001005236,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003944373,"about_ca_topic_score_gemma":0.00844312,"domain_scores_codex":[0.9994609,0.0001092438,0.00003764283,0.00007082035,0.0002176072,0.0001038215],"domain_scores_gemma":[0.9994092,0.0001050861,0.00004691271,0.0001977813,0.0001793313,0.00006167017],"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":[0.0004445658,0.0002471301,0.001943312,0.0002716548,0.0001145058,0.0003227467,0.0007860101,0.04111002,0.04095576,0.1687374,0.02849218,0.7165747],"study_design_scores_gemma":[0.00006447049,0.0001633266,0.001562089,0.0001446385,0.0001110773,0.0003493091,0.0003236578,0.7985704,0.02311496,0.1048725,0.07067072,0.00005281802],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.007391653,0.0001313974,0.9830382,0.00009606781,0.00005626714,0.00008644541,0.0001668424,0.002056373,0.006976782],"genre_scores_gemma":[0.138189,0.0002915826,0.8403365,0.000207025,0.00006970966,0.000174291,0.001133059,0.0008735002,0.01872531],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01097038,"threshold_uncertainty_score":0.03669959,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007502420502444573,"score_gpt":0.252234560907486,"score_spread":0.2447321404050414,"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."}}