{"id":"W2887906137","doi":"10.1109/tcomm.2018.2881117","title":"Learning-Aided Physical Layer Authentication as an Intelligent Process","year":2018,"lang":"en","type":"article","venue":"IEEE Transactions on Communications","topic":"Wireless Communication Security Techniques","field":"Engineering","cited_by":193,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"Engineering and Physical Sciences Research Council; Natural Sciences and Engineering Research Council of Canada; Ministère de la Défense Nationale","keywords":"Physical layer; Computer science; Authentication (law); Robustness (evolution); Authentication protocol; Lightweight Extensible Authentication Protocol; Distributed computing; Wireless","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0001927727,0.0002185572,0.0001880261,0.0002366408,0.000635119,0.00008672215,0.001435965,0.000121877,0.0001493897],"category_scores_gemma":[0.00001506061,0.0002479476,0.00009593413,0.0005377483,0.0003497142,0.0004099291,0.00000914202,0.000763182,0.0007114732],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001229294,"about_ca_system_score_gemma":0.00004290083,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003995196,"about_ca_topic_score_gemma":0.0001537179,"domain_scores_codex":[0.9987655,0.0002116823,0.0003275918,0.0002249505,0.0002339826,0.0002362822],"domain_scores_gemma":[0.9966355,0.0001907694,0.00006379557,0.002678695,0.0002963274,0.0001349178],"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":[0.0003087268,0.01239844,0.0001143878,0.0003073089,0.001039072,0.000002607997,0.1626357,0.07686958,0.190068,0.06250753,0.001646096,0.4921025],"study_design_scores_gemma":[0.0002815211,0.0005268172,0.0001537408,0.00009716392,0.00009226902,0.00001339419,0.001422589,0.551665,0.4221323,0.008951472,0.01405996,0.0006037456],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4905205,0.00008993396,0.485488,0.001232878,0.0002701748,0.0007871923,0.00002689641,0.004652125,0.01693231],"genre_scores_gemma":[0.9956302,0.0004464244,0.00303982,0.00007744042,0.00005578989,0.0004189911,0.00003345039,0.00007317318,0.0002247006],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5051097,"threshold_uncertainty_score":0.9999973,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03787961938960948,"score_gpt":0.336655443153291,"score_spread":0.2987758237636815,"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."}}