{"id":"W2964131227","doi":"10.1145/3351422.3351430","title":"RFID Hacking for Fun and Profit","year":2019,"lang":"en","type":"article","venue":"GetMobile Mobile Computing and Communications","topic":"RFID technology advancements","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Profit (economics); Hacker; Drone; Gesture; Feature (linguistics); Real-time computing; Embedded system; Computer hardware; Computer security; Artificial intelligence","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":[0.0001473642,0.0001251847,0.0001646337,0.00006375421,0.0002259068,0.0000355425,0.0003308952,0.00007518944,0.000005853548],"category_scores_gemma":[0.0000144068,0.000134591,0.00002435801,0.000107454,0.00009670616,0.00007991977,0.0003283822,0.0001827785,0.00001342843],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002396352,"about_ca_system_score_gemma":0.000006680443,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002854197,"about_ca_topic_score_gemma":0.00000411915,"domain_scores_codex":[0.999361,0.00001861373,0.0001899986,0.0001772558,0.00004394788,0.0002091716],"domain_scores_gemma":[0.9987925,0.0002221103,0.00003925429,0.000867597,0.00004104194,0.00003748721],"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":[0.00001547587,0.0001364357,0.1573926,0.0008492763,0.0003062901,8.358073e-7,0.002474615,0.04453219,0.02101639,0.03010203,0.001070971,0.7421029],"study_design_scores_gemma":[0.001681656,0.0002716589,0.01368723,0.000289688,0.00005597475,0.00003720363,0.001402091,0.8719371,0.002496734,0.003721972,0.1036725,0.0007462183],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9773328,0.006138203,0.01307967,0.0001065189,0.000155858,0.001093404,0.00001206885,0.0006365496,0.001444936],"genre_scores_gemma":[0.9803709,0.000511459,0.01862789,0.00003533295,0.00001557496,0.0002965903,0.00002380587,0.00002735256,0.00009108349],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8274049,"threshold_uncertainty_score":0.5488461,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00884535492063329,"score_gpt":0.2557899579207866,"score_spread":0.2469446030001533,"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."}}