{"id":"W2808349928","doi":"10.1109/isps.2018.8379018","title":"Towards privacy and ownership preserving of outsourced health data in IoT-cloud context","year":2018,"lang":"en","type":"preprint","venue":"","topic":"Cryptography and Data Security","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Outsourcing; Encryption; Computer science; Cloud computing; Computer security; Client-side encryption; Access control; Attribute-based encryption; Service provider; Context (archaeology); Information privacy; Service (business); On-the-fly encryption; Public-key cryptography; Business; Operating system","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":["open_science"],"consensus_categories":["open_science"],"category_scores_codex":[0.001973395,0.000267909,0.0005838135,0.0002708716,0.00006125725,0.000217392,0.005535509,0.0002065483,0.00004010424],"category_scores_gemma":[0.0002870316,0.0002292786,0.00006409643,0.0003360058,0.0001598303,0.0003343467,0.02204532,0.0005178656,0.000003026762],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003157057,"about_ca_system_score_gemma":0.0004276671,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007916758,"about_ca_topic_score_gemma":0.001940843,"domain_scores_codex":[0.9971336,0.0002646273,0.0006394116,0.0011902,0.0003865216,0.0003856977],"domain_scores_gemma":[0.9945598,0.0001413685,0.0003883681,0.004635699,0.00008760438,0.0001871197],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0002033534,0.001218387,0.08416735,0.006526035,0.0003765081,0.0000336867,0.06254701,0.0000343777,0.00005734896,0.4202113,0.09340034,0.3312243],"study_design_scores_gemma":[0.005342293,0.001039923,0.2690639,0.004875083,0.0000682572,0.00004465272,0.002112595,0.2951338,0.001161552,0.3054455,0.1120844,0.003627975],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1940826,0.004301267,0.785317,0.009060739,0.001415627,0.00144045,0.0008325629,0.0003085452,0.003241199],"genre_scores_gemma":[0.8736171,0.0003312767,0.1249511,0.0006548345,0.0001807326,0.00001001865,0.0002275276,0.00001379744,0.00001361133],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6795345,"threshold_uncertainty_score":0.999845,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09751251695423295,"score_gpt":0.332003215560051,"score_spread":0.234490698605818,"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."}}