{"id":"W4318766086","doi":"10.1109/jsen.2023.3240386","title":"Trust-Aware Virtual Network Embedding in Wireless Sensor Networks","year":2023,"lang":"en","type":"article","venue":"IEEE Sensors Journal","topic":"Software-Defined Networks and 5G","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Regina","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Quality of service; Computer network; Wireless sensor network; Network virtualization; Distributed computing; Virtual network; Throughput; Reliability (semiconductor); Virtualization; Wireless; Wireless network; Cloud computing","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008763933,0.0007496264,0.0007013344,0.0003617245,0.0004883075,0.0008219837,0.0009804434,0.0005551025,0.0006979404],"category_scores_gemma":[0.003473799,0.0003210767,0.0004714199,0.0004595507,0.0006995208,0.001899009,0.001405206,0.0007748961,0.0001191069],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000653457,"about_ca_system_score_gemma":0.0007993444,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002085002,"about_ca_topic_score_gemma":0.001949123,"domain_scores_codex":[0.9993178,0.0002775493,0.00004027985,0.0001129103,0.0001519854,0.00009949898],"domain_scores_gemma":[0.9986805,0.0006672574,0.0002157703,0.0001630536,0.0001794752,0.00009384149],"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":[0.00008680324,0.0000323232,0.0007714413,0.00006145031,0.00002484809,0.00007703965,0.00009132549,0.9413055,0.004589396,0.007823513,0.0003907823,0.04474565],"study_design_scores_gemma":[0.000002356414,0.00002505169,0.00005421268,0.000003144282,0.000004393319,0.00002278951,0.00001544691,0.9967713,0.0008401017,0.002051708,0.0002062632,0.000003213614],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05515651,0.0004307579,0.9425068,0.0001378011,0.00004707177,0.00004120406,0.00001850891,0.0002600742,0.001401142],"genre_scores_gemma":[0.9237774,0.0002650327,0.07483466,0.0000504258,0.00001630421,0.00005103091,0.00004268788,0.00004122527,0.0009212431],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002085002,"threshold_uncertainty_score":0.004741192,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01720002266298698,"score_gpt":0.2586758120346145,"score_spread":0.2414757893716276,"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."}}