{"id":"W3161684906","doi":"10.1109/jiot.2021.3079106","title":"Toward Privacy-Preserving Healthcare Monitoring Based on Time-Series Activities Over Cloud","year":2021,"lang":"en","type":"article","venue":"IEEE Internet of Things Journal","topic":"IoT and Edge/Fog Computing","field":"Computer Science","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of New Brunswick","funders":"Natural Science Foundation of Zhejiang Province; Natural Sciences and Engineering Research Council of Canada; Natural Science Foundation of Shaanxi Province; National Natural Science Foundation of China","keywords":"Computer science; Cloud computing; Health care; Computer security; Information privacy; Scheme (mathematics); Internet privacy","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0005600999,0.0002024799,0.0003100596,0.0001735694,0.0001574343,0.0005569835,0.001408585,0.00009078912,0.00001962845],"category_scores_gemma":[0.0001906622,0.0001925124,0.000199784,0.0002063403,0.00003757845,0.001248489,0.0005228476,0.0007024459,0.00001187741],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001577107,"about_ca_system_score_gemma":0.000229688,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006397627,"about_ca_topic_score_gemma":3.427069e-7,"domain_scores_codex":[0.9980568,0.0001697177,0.0004486039,0.0003020523,0.0006088431,0.0004139596],"domain_scores_gemma":[0.9985989,0.0002180691,0.0003618473,0.000445621,0.0002247303,0.0001508768],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001364607,0.00162517,0.09905477,0.00294105,0.001265052,0.006163107,0.196054,0.008023277,0.1856006,0.003081942,0.2565904,0.2382361],"study_design_scores_gemma":[0.00112331,0.0007563678,0.003569112,0.004649268,0.00002535677,0.0009393708,0.0003549854,0.2226598,0.7525703,0.003657655,0.008923423,0.0007710155],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7984402,0.000407008,0.1590398,0.004672623,0.03537301,0.00007527682,3.941392e-7,0.0001516387,0.001840124],"genre_scores_gemma":[0.9650499,0.00002112003,0.02958057,0.0004976991,0.003987798,0.000001355965,5.344427e-7,0.00002420147,0.0008368349],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5669697,"threshold_uncertainty_score":0.7850429,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02975106348768769,"score_gpt":0.2746602938593693,"score_spread":0.2449092303716816,"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."}}