{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001716383,0.0008380297,0.000389952,0.0008716874,0.002508369,0.006226465,0.001045583,0.002620029,0.03297967],"category_scores_gemma":[0.00862298,0.0003590418,0.0006171904,0.0007534842,0.003501794,0.009247479,0.006516572,0.003094752,0.02045286],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006734786,"about_ca_system_score_gemma":0.000534947,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00030882,"about_ca_topic_score_gemma":0.0003941698,"domain_scores_codex":[0.9977787,0.0006791885,0.0000683261,0.0002409004,0.000902774,0.0003301507],"domain_scores_gemma":[0.9946994,0.001304832,0.0005543925,0.002190706,0.0006400417,0.0006107059],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002141055,0.0001654097,0.004668084,0.0003541763,0.00006524588,0.001232774,0.004698884,0.0009084989,0.01004465,0.2530828,0.1870856,0.5374798],"study_design_scores_gemma":[0.00001099901,0.0001222947,0.001086869,0.0002960872,0.00002336998,0.002740831,0.001973782,0.001354482,0.0054577,0.04941817,0.9374608,0.00005463489],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.04109811,0.01118513,0.1443739,0.06054662,0.008012691,0.000181687,0.0001775702,0.006914238,0.7275101],"genre_scores_gemma":[0.529157,0.008091523,0.05089447,0.01880796,0.003187822,0.0001615167,0.0002327056,0.00184463,0.3876224],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.03297967,"threshold_uncertainty_score":0.110328,"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."}}