{"id":"W1972820158","doi":"10.1155/2012/793194","title":"On Optimal Antijamming Strategies in Sensor Networks","year":2012,"lang":"en","type":"article","venue":"International Journal of Distributed Sensor Networks","topic":"Security in Wireless Sensor Networks","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Key Research and Development Program of China; National High-tech Research and Development Program; Beihang University; National Natural Science Foundation of China; Federation for the Humanities and Social Sciences","keywords":"Jamming; Computer science; Nash equilibrium; Wireless sensor network; Computer network; Channel (broadcasting); Wireless; Game theory; Strategy; Dominance (genetics); Wireless network; Best response; Computer security; Telecommunications; Mathematical optimization","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0009881805,0.0004178257,0.0005586434,0.0004566529,0.0001023579,0.0005744917,0.001960336,0.0003413683,0.00004430311],"category_scores_gemma":[0.0002072209,0.0003963245,0.0003130697,0.0006793977,0.0001123175,0.001428188,0.0002680283,0.001431236,0.00001849882],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003793195,"about_ca_system_score_gemma":0.00008932735,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001820629,"about_ca_topic_score_gemma":0.00000707603,"domain_scores_codex":[0.995976,0.0003198112,0.001234729,0.0003612303,0.001115094,0.0009931691],"domain_scores_gemma":[0.9966997,0.000965292,0.0009034522,0.0004556281,0.0006181356,0.0003578104],"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":[0.0001922404,0.0003488705,0.003866419,0.000003202626,0.0001857125,0.0006515583,0.0003287529,0.9710795,0.0000496719,0.01692258,0.002338646,0.004032821],"study_design_scores_gemma":[0.002168474,0.0002570201,0.01669868,0.0004299699,0.00003494838,0.001616886,0.0006928899,0.9740788,0.0002018203,0.000433785,0.002683742,0.0007029203],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2219615,0.0008551893,0.7697378,0.0008394457,0.006005657,0.00014086,0.00001833241,0.0000824806,0.0003587616],"genre_scores_gemma":[0.9838306,0.0003045944,0.01252053,0.0004346872,0.002812373,0.000003295633,0.00004626573,0.00003422552,0.00001340336],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7618691,"threshold_uncertainty_score":0.9998488,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01244685736556535,"score_gpt":0.2659790359810574,"score_spread":0.2535321786154921,"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."}}