{"id":"W4409456782","doi":"10.69709/caic.2025.181989","title":"A Novel Transformer Reinforcement Learning-Based NFV Service Placement in MEC Networks","year":2025,"lang":"en","type":"article","venue":"Computing&AI Connect","topic":"Advancements in Semiconductor Devices and Circuit Design","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University; École de Technologie Supérieure","funders":"","keywords":"Transformer; Reinforcement learning; Computer science; Reinforcement; Artificial intelligence; Engineering; Structural engineering; Electrical engineering; Voltage","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003347358,0.0003175389,0.0003501901,0.0001942739,0.0001141548,0.00005847825,0.0002993078,0.0001229016,0.0001765625],"category_scores_gemma":[0.00001869376,0.0003456035,0.0000796488,0.0006633473,0.0000221545,0.0001032963,0.00002780067,0.0004811617,0.0000173939],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002638858,"about_ca_system_score_gemma":0.00006196801,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005012728,"about_ca_topic_score_gemma":0.00007972302,"domain_scores_codex":[0.9983276,0.00003487095,0.0005364127,0.000348049,0.0001885867,0.0005645479],"domain_scores_gemma":[0.9993244,0.0001947551,0.00005817092,0.000282141,0.00006944914,0.00007101404],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002372773,0.00003910815,0.0005535114,0.0001802471,0.00006953033,0.000003740102,0.0002323331,0.9904457,0.002236088,0.0006516004,0.0004937524,0.00507061],"study_design_scores_gemma":[0.001982304,0.00005945807,0.0002182765,0.0003679527,0.00002947848,0.00000160551,0.0001626592,0.9718454,0.002056909,0.00003886788,0.0228663,0.0003707442],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03117151,0.0006715289,0.9593681,0.0001434935,0.0008631841,0.0005269735,0.000001543786,0.0003544958,0.006899178],"genre_scores_gemma":[0.9969257,0.00002590444,0.0004038138,0.0022483,0.00007646094,0.0000340845,0.00003705346,0.00004055603,0.0002081965],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9657541,"threshold_uncertainty_score":0.9998996,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01267217141504063,"score_gpt":0.2465596082104549,"score_spread":0.2338874367954143,"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."}}