{"id":"W4382318739","doi":"10.1609/aaai.v37i12.26684","title":"Neighbor Auto-Grouping Graph Neural Networks for Handover Parameter Configuration in Cellular Network","year":2023,"lang":"en","type":"article","venue":"Proceedings of the AAAI Conference on Artificial Intelligence","topic":"Advanced MIMO Systems Optimization","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; University of Alberta","funders":"","keywords":"Handover; Computer science; Cellular network; Network performance; Key (lock); Graph; Distributed computing; Artificial intelligence; Machine learning; Theoretical computer science; 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":[0.0005419899,0.0008310311,0.0006147429,0.0004486788,0.0003539236,0.0004569225,0.001035966,0.0009139068,0.001040558],"category_scores_gemma":[0.001601133,0.0003493,0.0004154365,0.0004708559,0.0006204058,0.0008050803,0.0006522752,0.0009109721,0.0001496215],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001169905,"about_ca_system_score_gemma":0.0007737299,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01812167,"about_ca_topic_score_gemma":0.0173101,"domain_scores_codex":[0.9997707,0.0000580765,0.00001008143,0.00006614069,0.00004292912,0.00005209734],"domain_scores_gemma":[0.9996204,0.0001755379,0.00006499283,0.00002988432,0.00008204776,0.00002710222],"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":[0.00002524766,0.00001796147,0.0005540216,0.0000123167,0.00001317985,0.0000193609,0.00001603181,0.9833628,0.0005259965,0.001040434,0.0003014464,0.01411115],"study_design_scores_gemma":[0.000001248985,0.00000505808,0.00006619954,9.399641e-7,0.000002431835,0.000002287532,0.000001632071,0.9992127,0.00009700959,0.0005727725,0.0000364901,0.000001201537],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.144537,0.001090772,0.8484276,0.0006190524,0.00008578147,0.00005857838,0.0001329071,0.001116396,0.003931891],"genre_scores_gemma":[0.9658621,0.0001900462,0.03180116,0.0001194298,0.00002408728,0.00004465825,0.0001470296,0.0000412453,0.001770266],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01812167,"threshold_uncertainty_score":0.03603238,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04674955456329356,"score_gpt":0.2638844310902445,"score_spread":0.2171348765269509,"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."}}