{"id":"W4387918077","doi":"10.1109/twc.2023.3325384","title":"Achieving Covert Communication in Large-Scale SWIPT-Enabled D2D Networks","year":2023,"lang":"en","type":"article","venue":"IEEE Transactions on Wireless Communications","topic":"Wireless Communication Security Techniques","field":"Engineering","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba; Artificial Intelligence in Medicine (Canada); Ericsson (Canada)","funders":"National Natural Science Foundation of China; National Research Foundation Singapore","keywords":"Computer science; Covert; Wireless; Computer network; Scale (ratio); Telecommunications","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":[0.0008957548,0.0003844758,0.0004655083,0.000863024,0.0008143255,0.0001340928,0.002783954,0.0003466515,0.00006850413],"category_scores_gemma":[0.000009594075,0.0004802779,0.0001902805,0.002628203,0.00021724,0.0005682879,0.00006340001,0.001721952,0.0002377048],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003618094,"about_ca_system_score_gemma":0.00004935358,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001339573,"about_ca_topic_score_gemma":0.003105613,"domain_scores_codex":[0.997339,0.0005112856,0.0008522085,0.0003302225,0.0003167373,0.0006505743],"domain_scores_gemma":[0.9932679,0.0009157002,0.0001164728,0.005418299,0.0001347635,0.0001468488],"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":[0.00007139337,0.001757744,0.001496856,0.0001939366,0.000278476,0.000006576953,0.008403669,0.8941832,0.007559209,0.005916895,0.005889961,0.07424213],"study_design_scores_gemma":[0.000808618,0.00003236435,0.002083715,0.0003723054,0.00003580052,0.000006323498,0.0008766609,0.9824212,0.003059373,0.0002959868,0.009382699,0.0006249396],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1515268,0.001380343,0.8262279,0.002825203,0.0003983674,0.001428728,0.0001649613,0.0074749,0.00857284],"genre_scores_gemma":[0.9743546,0.019396,0.004469573,0.0001709221,0.00001610015,0.001041715,0.0002078801,0.0001420733,0.0002011193],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8228278,"threshold_uncertainty_score":0.9997649,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0191228628948837,"score_gpt":0.2626043478042409,"score_spread":0.2434814849093572,"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."}}