{"id":"W2121452655","doi":"10.1109/icdcsw.2007.91","title":"A Cooperative Approach for Analyzing Intrusions in Mobile Ad hoc Networks","year":2007,"lang":"en","type":"article","venue":"","topic":"Mobile Ad Hoc Networks","field":"Computer Science","cited_by":39,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"False positive paradox; Computer science; Mobile ad hoc network; Intrusion detection system; Node (physics); Class (philosophy); Game theory; Reputation; Shapley value; Wireless ad hoc network; Computer security; Artificial intelligence; Mathematics; Wireless; 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":[0.001041766,0.0001671161,0.0002371238,0.0001531553,0.0001400307,0.0001182663,0.0007043341,0.0001228629,0.00002324697],"category_scores_gemma":[0.00003071219,0.0001441931,0.00007387491,0.001141849,0.00004303684,0.0003459465,0.0003033354,0.0002447317,0.000005438038],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008760299,"about_ca_system_score_gemma":0.00004852999,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000597665,"about_ca_topic_score_gemma":0.0002487937,"domain_scores_codex":[0.9983363,0.0000501231,0.0003604287,0.0005308181,0.0001382926,0.0005840024],"domain_scores_gemma":[0.9988167,0.0003648709,0.00006716137,0.0005188167,0.0000987761,0.000133724],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00004334907,0.000276646,0.0008048468,0.00001029168,0.000029393,0.00002174668,0.001241509,0.3713087,0.00009223068,0.04673611,0.003132753,0.5763024],"study_design_scores_gemma":[0.0004883016,0.00014767,0.0003759984,0.00001253243,0.000003620285,0.000007659453,0.0001440266,0.9903787,0.0001113396,0.0002229705,0.007888936,0.000218245],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.004631179,0.00214193,0.9878496,0.00004575935,0.0001755961,0.0009585175,7.043943e-7,0.0001432251,0.004053496],"genre_scores_gemma":[0.5889034,0.0002071187,0.4092758,0.0004671664,0.000156589,0.0003814918,0.00001274221,0.00001749746,0.0005781407],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.61907,"threshold_uncertainty_score":0.5880026,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01513698251937869,"score_gpt":0.2645134588495537,"score_spread":0.249376476330175,"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."}}