{"id":"W1999113345","doi":"10.1145/1753846.1753917","title":"Visible and controllable RFID tags","year":2010,"lang":"en","type":"article","venue":"","topic":"Interactive and Immersive Displays","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"Microsoft Research","keywords":"Radio-frequency identification; Computer science; Computer security; Identification (biology); Simple (philosophy); Control (management); Internet privacy; Information sensitivity; Human–computer interaction; 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":[0.00007068641,0.00005422246,0.00006625077,0.00003517446,0.0000628676,0.0001057791,0.0002126575,0.00002505029,0.0002232312],"category_scores_gemma":[0.00002381307,0.00004221894,0.00001949727,0.00007239651,0.00002183544,0.0004946494,0.00009342465,0.00009551362,0.000201708],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000002802038,"about_ca_system_score_gemma":0.00001632633,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005196508,"about_ca_topic_score_gemma":0.00002037561,"domain_scores_codex":[0.9995762,0.000007815303,0.0000575847,0.0001602863,0.00006357705,0.0001345268],"domain_scores_gemma":[0.9996217,0.0000463855,0.00001865989,0.0001923786,0.00007090245,0.00004990364],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.000004745807,0.00001914236,0.001089762,0.000001660015,0.000008651195,0.000003766112,0.000127803,3.042077e-7,0.6817679,0.3071798,0.00820622,0.001590304],"study_design_scores_gemma":[0.001710986,0.0002549141,0.03692418,0.000008370464,0.000008983793,0.00007609316,0.0001817062,0.03030108,0.7321563,0.01038454,0.1875412,0.000451627],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.3704149,0.00005660773,0.1953681,0.003473082,0.001277229,0.0001659776,0.000001894532,0.00005278038,0.4291894],"genre_scores_gemma":[0.9889778,0.000002856581,0.005177656,0.001605263,0.00003509404,0.00000301434,3.811758e-7,0.000002424845,0.004195528],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6185629,"threshold_uncertainty_score":0.2592616,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003358135729313039,"score_gpt":0.2210197537788152,"score_spread":0.2176616180495022,"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."}}