{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004087213,0.0008619986,0.0002684396,0.0004408313,0.0003961809,0.001438976,0.001135795,0.00103042,0.007332171],"category_scores_gemma":[0.001426407,0.0004851117,0.0005124591,0.0003413032,0.000766211,0.00202211,0.001522211,0.001119032,0.002133147],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000275027,"about_ca_system_score_gemma":0.0001836269,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002849613,"about_ca_topic_score_gemma":0.0003311785,"domain_scores_codex":[0.9992504,0.0001090672,0.0000332609,0.0001508108,0.000362052,0.00009447529],"domain_scores_gemma":[0.9992673,0.0002295825,0.0001282801,0.0001450129,0.000130398,0.00009942499],"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":[0.0003769528,0.0001292259,0.0005404096,0.0006148408,0.00002075517,0.0006276857,0.0004688267,0.003196947,0.8521999,0.04018533,0.006141809,0.09549736],"study_design_scores_gemma":[0.0001777357,0.001021155,0.002025277,0.0001754451,0.00007364792,0.002021821,0.0003345255,0.01993437,0.7389403,0.009320604,0.2257751,0.000199963],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1492527,0.00492105,0.7486993,0.001039344,0.001515351,0.0002558665,0.0007223302,0.006870902,0.08672317],"genre_scores_gemma":[0.7136161,0.003385891,0.2318994,0.0007567079,0.0003555249,0.0004551068,0.0005689058,0.0007802927,0.04818206],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007332171,"threshold_uncertainty_score":0.02452856,"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."}}