{"id":"W1998745036","doi":"10.1109/glocom.2014.7036829","title":"Exploiting channel-aware reputation system against selective forwarding attacks in WSNs","year":2014,"lang":"en","type":"article","venue":"","topic":"Mobile Ad Hoc Networks","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"U.S. Department of Homeland Security","keywords":"Packet forwarding; Computer network; Computer science; Network packet; Packet loss; Wireless sensor network; Throughput; Node (physics); Channel (broadcasting); Reputation; Wireless; Telecommunications; Engineering","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":[],"consensus_categories":[],"category_scores_codex":[0.0008298858,0.0001552607,0.0002224311,0.000159616,0.0001298293,0.0001582055,0.0004641904,0.00008603871,0.000001665294],"category_scores_gemma":[0.00006603412,0.0001520264,0.0000569358,0.0006753851,0.00001221055,0.0007264682,0.0002050051,0.0001839368,0.00004081042],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002616362,"about_ca_system_score_gemma":0.00003292536,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004281757,"about_ca_topic_score_gemma":0.0000555178,"domain_scores_codex":[0.9982882,0.0001707026,0.0003416085,0.000529595,0.0002501471,0.0004197257],"domain_scores_gemma":[0.9990382,0.0002214239,0.0001405003,0.0004011131,0.0001168129,0.00008198234],"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":[0.00001639468,0.0001059272,0.003818099,0.0002888908,0.00006372573,0.00007934849,0.009439271,0.630089,0.0004383758,0.1296589,0.002492621,0.2235094],"study_design_scores_gemma":[0.0002678721,0.00004279528,0.0005144912,0.0001652296,0.000001963368,0.0000103019,0.0005762944,0.9967731,0.0009543608,0.0003795472,0.000126821,0.0001872219],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01732663,0.00001417387,0.9622973,0.0001102057,0.0003570069,0.0002906341,2.876026e-7,0.0004774359,0.01912639],"genre_scores_gemma":[0.9925666,0.000002468333,0.006789018,0.0002170464,0.0002009562,0.00009540659,0.000003768226,0.00001661529,0.0001081316],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9752399,"threshold_uncertainty_score":0.6199456,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01148025954126442,"score_gpt":0.2299840595182338,"score_spread":0.2185037999769694,"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."}}