{"id":"W4405933906","doi":"10.1109/ojcoms.2024.3524497","title":"Concept Drift Aware Wireless Key Generation in Dynamic LiFi Networks","year":2024,"lang":"en","type":"article","venue":"IEEE Open Journal of the Communications Society","topic":"Energy Efficient Wireless Sensor Networks","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"National Science Foundation","keywords":"Key (lock); Computer science; Wireless; Wireless network; Computer network; Telecommunications; Computer security","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":[0.002500015,0.0006047601,0.0006805122,0.0005070077,0.0005286401,0.0009133135,0.001373249,0.0007737963,0.0006562149],"category_scores_gemma":[0.006638112,0.0003367775,0.0003644075,0.0005082931,0.001153735,0.003832067,0.001845052,0.001414369,0.0002129409],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001364688,"about_ca_system_score_gemma":0.0007673067,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008637671,"about_ca_topic_score_gemma":0.0006775025,"domain_scores_codex":[0.9988759,0.0003409699,0.00004070433,0.000211236,0.0003136716,0.0002175132],"domain_scores_gemma":[0.9972637,0.001550536,0.0004676784,0.000330377,0.0002713854,0.0001163171],"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":[0.0002936349,0.00009593184,0.002006045,0.0001000893,0.00004108356,0.0001821324,0.0002044496,0.8719914,0.01447078,0.02296914,0.0007642331,0.08688108],"study_design_scores_gemma":[0.000004792118,0.00006043383,0.0001884861,0.000005059705,0.000005076826,0.000077713,0.00002772,0.9898195,0.004974028,0.004504655,0.0003235529,0.000009103831],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1378569,0.0005120782,0.858919,0.0003365501,0.00003986226,0.00006458398,0.00006000956,0.0003320178,0.001878925],"genre_scores_gemma":[0.9667158,0.0001656033,0.03210443,0.0000797067,0.00001884058,0.00003760607,0.00004331963,0.00001860711,0.0008161154],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002500015,"threshold_uncertainty_score":0.0132215,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03346167307846352,"score_gpt":0.3047237125567392,"score_spread":0.2712620394782757,"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."}}