{"id":"W2012264225","doi":"10.5555/1400549.1400705","title":"Modeling privacy compromise: visibility of individuals via DRM and RFID in ubiquitous computing","year":2008,"lang":"en","type":"article","venue":"Spring Simulation Multiconference","topic":"RFID technology advancements","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Compromise; Computer science; Ubiquitous computing; Information privacy; Radio-frequency identification; Visibility; Computer security; Internet privacy; Digital rights management; Frontier; Privacy software; Identification (biology); Privacy protection; Human–computer interaction","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":[0.0001798347,0.0001534691,0.0002576437,0.0001765333,0.00006391954,0.00000888732,0.0001639651,0.0001093762,0.000005454683],"category_scores_gemma":[0.0001857063,0.0001828724,0.00002010938,0.0001609919,0.00008047228,0.000191772,0.0001165017,0.0002187175,0.000002844133],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006144095,"about_ca_system_score_gemma":0.0000127597,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005760586,"about_ca_topic_score_gemma":0.00001112212,"domain_scores_codex":[0.9988779,0.00002595124,0.0004793776,0.0002459729,0.0001460452,0.0002246967],"domain_scores_gemma":[0.9993936,0.0001304937,0.0000641833,0.0002892675,0.00008330279,0.00003914396],"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":[0.000003558696,0.00002227354,0.2005731,0.00005595781,0.000008388331,0.000001419803,0.000537539,0.7872621,0.007591947,0.00005157836,3.560825e-8,0.003892041],"study_design_scores_gemma":[0.0006240422,0.00001044939,0.1677857,0.00007069351,0.000003620885,9.974467e-7,0.00001584209,0.8270913,0.003959104,0.0003057194,0.000002764795,0.0001297808],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7432949,0.00008266813,0.2561491,0.000003850272,0.00006296078,0.0002097304,0.00000162901,0.0001741822,0.00002104175],"genre_scores_gemma":[0.9776226,0.00002301345,0.02231253,0.000004138613,0.00001190944,0.000003994277,0.000002405902,0.00001833055,0.000001114259],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2343277,"threshold_uncertainty_score":0.7457322,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03067914753982292,"score_gpt":0.2771446830812125,"score_spread":0.2464655355413896,"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."}}