{"id":"W2492668260","doi":"10.12694/scpe.v17i3.1180","title":"Analysis and Verification of XACML Policies in a Medical Cloud Environment","year":2016,"lang":"en","type":"article","venue":"Scalable Computing Practice and Experience","topic":"Big Data and Business Intelligence","field":"Business, Management and Accounting","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Sherbrooke","funders":"Bundesministerium für Bildung und Forschung; Deutscher Akademischer Austauschdienst","keywords":"XACML; Cloud computing; Computer science; Computer security; Operating system; Authorization","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":[0.02278592,0.0008973774,0.0008342214,0.00314914,0.002327862,0.0051259,0.002226897,0.001717423,0.00148142],"category_scores_gemma":[0.04828126,0.0009642532,0.001656109,0.001670062,0.002771664,0.005271738,0.002831602,0.002434588,0.0006213182],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004349443,"about_ca_system_score_gemma":0.01306298,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01616313,"about_ca_topic_score_gemma":0.01176537,"domain_scores_codex":[0.9702367,0.009833978,0.00298274,0.002837816,0.01188332,0.00222544],"domain_scores_gemma":[0.9501014,0.0267377,0.006246201,0.009212751,0.006718664,0.0009832942],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.002369757,0.001425758,0.06659545,0.001276282,0.0004286219,0.004072709,0.004494471,0.3408057,0.06164511,0.1699325,0.01107799,0.3358757],"study_design_scores_gemma":[0.0001711699,0.0001498012,0.00320106,0.0001368713,0.00006555505,0.0004212882,0.000440187,0.9020787,0.05655327,0.02907027,0.007621287,0.00009049237],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1563841,0.0003184463,0.8175232,0.002336192,0.0001415969,0.001005186,0.0008417242,0.01827773,0.003171827],"genre_scores_gemma":[0.5295021,0.0002034781,0.4670308,0.0004240929,0.00005473694,0.0002519131,0.0007839123,0.000533313,0.001215794],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02278592,"threshold_uncertainty_score":0.1205049,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03458922695781805,"score_gpt":0.3084640098878952,"score_spread":0.2738747829300771,"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."}}