{"id":"W4205608052","doi":"10.33969/j-nana.2021.010304","title":"Embedded Contact Tracing using Mobile Devices, Cloud, and iBeacons","year":2021,"lang":"en","type":"article","venue":"Journal of Networking and Network Applications","topic":"COVID-19 Digital Contact Tracing","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Contact tracing; Beacon; Cloud computing; Computer science; Tracing; Computer security; Mobile device; Implementation; Coronavirus disease 2019 (COVID-19); Safeguard; Computer network; Operating system; Business","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":[0.0004098959,0.0005440169,0.0006084539,0.0009575813,0.0009000118,0.001623812,0.001660651,0.0006731184,0.003067286],"category_scores_gemma":[0.001662465,0.0002252556,0.0002854338,0.001144128,0.000346444,0.002112322,0.002383511,0.0003944876,0.001186965],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006890659,"about_ca_system_score_gemma":0.0008957889,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002834636,"about_ca_topic_score_gemma":0.003235377,"domain_scores_codex":[0.9991781,0.0001260463,0.00004332937,0.0001820788,0.0002947156,0.0001757188],"domain_scores_gemma":[0.9990655,0.0001343805,0.0001498051,0.0003759474,0.0001668818,0.0001075346],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00137214,0.0005568218,0.0212081,0.0005574142,0.0001749035,0.002172301,0.0009130405,0.02225557,0.05718474,0.0468202,0.03555373,0.8112311],"study_design_scores_gemma":[0.0002178042,0.0009308637,0.01498459,0.0003992644,0.0002435177,0.003338338,0.001790576,0.7070144,0.09430888,0.02758058,0.1490037,0.0001875936],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2127343,0.004423823,0.6989021,0.001667942,0.0006168644,0.0009216251,0.001001699,0.0137011,0.06603058],"genre_scores_gemma":[0.9225723,0.0005856436,0.06855052,0.0003146574,0.00005937114,0.0001397293,0.0003663453,0.00009184295,0.007319551],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003067286,"threshold_uncertainty_score":0.01026112,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02402530814310435,"score_gpt":0.2870463216493589,"score_spread":0.2630210135062546,"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."}}