{"id":"W2055112977","doi":"10.1109/infcom.2012.6195818","title":"Location privacy preservation in collaborative spectrum sensing","year":2012,"lang":"en","type":"article","venue":"","topic":"Cognitive Radio Networks and Spectrum Sensing","field":"Computer Science","cited_by":102,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Testbed; Overhead (engineering); Protocol (science); Geolocation; Participatory sensing; Differential privacy; Scheme (mathematics); Information privacy; Computer network; Computer security; Data mining; World Wide Web","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":[0.00679824,0.0007785677,0.001099682,0.0007677919,0.001102257,0.002194892,0.002506194,0.001684594,0.0005928235],"category_scores_gemma":[0.01882484,0.000586677,0.001007002,0.001179134,0.002620828,0.004923039,0.004669087,0.00156434,0.0002998781],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001001122,"about_ca_system_score_gemma":0.00129277,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004541232,"about_ca_topic_score_gemma":0.0002761337,"domain_scores_codex":[0.989402,0.004453988,0.0006479006,0.001954642,0.002864717,0.0006768134],"domain_scores_gemma":[0.9765058,0.008672492,0.003265634,0.009891454,0.001316523,0.0003479689],"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":[0.001462038,0.000348182,0.008561937,0.0004380229,0.0003202364,0.001213167,0.001893523,0.4010722,0.08434919,0.285162,0.002115275,0.2130642],"study_design_scores_gemma":[0.00009648158,0.0005030782,0.001174032,0.0000379886,0.00009804741,0.0009076862,0.0002909753,0.8292998,0.05269177,0.1114429,0.003382044,0.00007522382],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0320177,0.0001285019,0.9661588,0.0002138274,0.00001959433,0.00004811406,0.00004188323,0.0001979327,0.001173506],"genre_scores_gemma":[0.9145079,0.0001100664,0.08436048,0.0001019681,0.00004421545,0.00009055142,0.00005609018,0.00002169885,0.0007069825],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00679824,"threshold_uncertainty_score":0.03595293,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01696022249156344,"score_gpt":0.2519636560893667,"score_spread":0.2350034335978033,"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."}}