{"id":"W4396506601","doi":"10.1109/lwc.2024.3395511","title":"Efficient User-Centric AP Clustering Through Stable UE-AP Matching for Indoor VLC Systems","year":2024,"lang":"en","type":"article","venue":"IEEE Wireless Communications Letters","topic":"Optical Wireless Communication Technologies","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"Basic and Applied Basic Research Foundation of Guangdong Province; National Natural Science Foundation of China; Natural Science Foundation of Xiamen City","keywords":"Computer science; Visible light communication; Cluster analysis; Matching (statistics); Computer network; Light-emitting diode; Artificial intelligence; Optoelectronics; Mathematics; Physics","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":[0.001223342,0.0007439562,0.0008797119,0.0006191623,0.0008305257,0.001169794,0.001848746,0.0009703754,0.00124596],"category_scores_gemma":[0.003540797,0.0003774018,0.0003759803,0.001365711,0.0006588237,0.001206531,0.001879263,0.0009503578,0.0006494909],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008624857,"about_ca_system_score_gemma":0.001057634,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001199159,"about_ca_topic_score_gemma":0.001278346,"domain_scores_codex":[0.9986838,0.0004501426,0.00005389745,0.0002256642,0.0003291596,0.0002573023],"domain_scores_gemma":[0.9985709,0.0004670569,0.0002999072,0.0002925724,0.0002580339,0.0001115104],"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":[0.0004028149,0.0002260248,0.001469359,0.0001718743,0.0001039684,0.0002537661,0.0002146885,0.7373103,0.05959663,0.04989135,0.002980352,0.1473788],"study_design_scores_gemma":[0.00001435047,0.0001551113,0.0002139304,0.000005069423,0.00001418592,0.0001634994,0.00003682441,0.9839258,0.008805636,0.005580036,0.001069248,0.00001630443],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03183555,0.0001772128,0.9654545,0.00009622645,0.00002801332,0.00006233245,0.000028822,0.0003293336,0.00198808],"genre_scores_gemma":[0.9240731,0.0001340491,0.07412686,0.00008057556,0.00003195064,0.00006395094,0.00004086027,0.00003117534,0.001417473],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001848746,"threshold_uncertainty_score":0.006469727,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02721806618472933,"score_gpt":0.2658453725123714,"score_spread":0.2386273063276421,"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."}}