{"id":"W2126926086","doi":"10.1109/wcnc.2008.493","title":"A Mechanism Design-Based Multi-Leader Election Scheme for Intrusion Detection in MANET","year":2008,"lang":"en","type":"article","venue":"","topic":"Mobile Ad Hoc Networks","field":"Computer Science","cited_by":28,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Mobile ad hoc network; Node (physics); Incentive; Computer science; Reputation; Intrusion detection system; Computer network; Wireless ad hoc network; Resource (disambiguation); Scheme (mathematics); Resource allocation; Computer security; Process (computing); Resource consumption; Distributed computing; Microeconomics; Economics; Engineering; Wireless; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004552251,0.0005819818,0.001097339,0.001153282,0.001200119,0.001263537,0.002702977,0.001465187,0.001109659],"category_scores_gemma":[0.006845681,0.0003890544,0.0008186873,0.001065918,0.0009440864,0.00253211,0.001274053,0.001120039,0.0003028382],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008772759,"about_ca_system_score_gemma":0.001126873,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003662605,"about_ca_topic_score_gemma":0.0003608481,"domain_scores_codex":[0.9976992,0.001103205,0.000182162,0.0003396895,0.0005186269,0.000156964],"domain_scores_gemma":[0.9965937,0.001370003,0.0006067212,0.0005823945,0.0006358559,0.0002113627],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0008762841,0.0008633422,0.00462742,0.001238645,0.0006088032,0.001042863,0.001192949,0.2530012,0.04772243,0.3420298,0.009649254,0.3371471],"study_design_scores_gemma":[0.0003704689,0.001049226,0.0006218884,0.00005747094,0.0002155207,0.001123632,0.0001108099,0.9234992,0.01129246,0.04051664,0.02103842,0.0001042215],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01643671,0.0006733618,0.9797737,0.0004253844,0.0002011055,0.0003530944,0.00003539777,0.000384598,0.001716663],"genre_scores_gemma":[0.688504,0.000743659,0.3063231,0.0003478,0.000170104,0.0006924578,0.0001076424,0.00003664754,0.003074684],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004552251,"threshold_uncertainty_score":0.02407485,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0411875585090779,"score_gpt":0.2502001528663985,"score_spread":0.2090125943573206,"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."}}