{"id":"W2897779970","doi":"10.1145/3241539.3241561","title":"Challenge","year":2018,"lang":"en","type":"article","venue":"","topic":"RFID technology advancements","field":"Engineering","cited_by":64,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Radio-frequency identification; Software deployment; Identification (biology); Reading (process); Protocol (science); Task (project management); Embedded system; Wireless sensor network; Battery (electricity); Human–computer interaction; Computer hardware; Computer security; Computer network; Engineering; Systems engineering; Software engineering","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.000009947179,0.00002752142,0.00002356654,0.00002010935,0.00001018187,0.000001231542,0.00005081548,0.0000258807,0.0004964426],"category_scores_gemma":[0.000002203498,0.0000261641,0.000004330309,0.00003501085,0.00002270346,0.00003250457,0.000009631823,0.00002692091,0.00119117],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000007681928,"about_ca_system_score_gemma":4.649218e-7,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":2.827781e-7,"about_ca_topic_score_gemma":0.000006358192,"domain_scores_codex":[0.999839,5.570343e-7,0.00002951488,0.00003598218,0.0000201743,0.00007477958],"domain_scores_gemma":[0.9998811,0.000001801097,0.000001475055,0.0001006002,0.000005850799,0.00000912081],"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":[0.000006594974,0.00008871917,0.00336459,0.00005425562,0.0001831185,0.00002271097,0.0004531159,0.0003371088,0.05191528,0.2636907,0.1042409,0.5756428],"study_design_scores_gemma":[0.0003970461,0.0001250138,0.001763153,0.00000793634,0.000003913518,0.000004864185,0.00004319461,0.01389719,0.1997867,0.01650927,0.7671904,0.0002713025],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.1162551,0.0001358719,0.02715766,0.0001717688,0.0004131826,0.00004475406,3.450914e-7,0.002035727,0.8537856],"genre_scores_gemma":[0.9957417,0.0000231315,0.0035157,0.00002651584,0.00004164852,0.000003743037,2.00453e-7,0.000006706195,0.000640623],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8794866,"threshold_uncertainty_score":0.9995865,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007993276121453034,"score_gpt":0.2155728175621771,"score_spread":0.2075795414407241,"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."}}