{"id":"W2086883455","doi":"10.1002/sec.122","title":"PCM: a privacy‐preserving detection mechanism in mobile<i>ad hoc</i>networks","year":2009,"lang":"en","type":"article","venue":"Security and Communication Networks","topic":"Privacy-Preserving Technologies in Data","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Anonymity; Computer security; Witness; Revocation; Mobile ad hoc network; Wireless ad hoc network; Internet privacy; Vehicular ad hoc network; Computer network; Overhead (engineering); Network packet; Telecommunications; Wireless","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":[0.002575352,0.000421975,0.0005229556,0.0007271739,0.001002385,0.001443828,0.001799046,0.001122675,0.001083454],"category_scores_gemma":[0.005709174,0.0002604458,0.0003877161,0.0007066749,0.001708666,0.002926127,0.002985759,0.0009290175,0.0003191914],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004834996,"about_ca_system_score_gemma":0.0008990805,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003838758,"about_ca_topic_score_gemma":0.0002141228,"domain_scores_codex":[0.9984645,0.0005426307,0.00009979626,0.0002337175,0.0005319232,0.0001275074],"domain_scores_gemma":[0.996356,0.001224703,0.0008140644,0.001044341,0.0003688094,0.0001920746],"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":[0.002044314,0.0004916832,0.007326125,0.0008079441,0.0001750663,0.002177669,0.001899804,0.1227466,0.0971404,0.3430299,0.01669335,0.405467],"study_design_scores_gemma":[0.0002291172,0.001300421,0.001465599,0.0001089447,0.0001066487,0.00215498,0.000299147,0.8053349,0.06201456,0.08277807,0.04409141,0.0001161874],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06938408,0.0007103058,0.9210562,0.0008267986,0.0001832315,0.0003294885,0.0001329309,0.002580824,0.004796159],"genre_scores_gemma":[0.8890934,0.0003869573,0.1072251,0.0002999858,0.0001407768,0.0001901432,0.0001173274,0.00004553077,0.002500723],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002575352,"threshold_uncertainty_score":0.01361996,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01421798326802722,"score_gpt":0.2499924887752912,"score_spread":0.235774505507264,"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."}}