{"id":"W2109871184","doi":"10.1109/hicss.2007.207","title":"Enabling Web Services Policy Negotiation with Privacy preserved using XACML","year":2007,"lang":"en","type":"article","venue":"","topic":"Access Control and Trust","field":"Social Sciences","cited_by":24,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ontario Tech University","funders":"National Natural Science Foundation of China","keywords":"XACML; Negotiation; Computer science; Privacy policy; Enforcement; Web service; Context (archaeology); Information privacy; Markup language; Access control; Knowledge management; World Wide Web; Computer security; XML; Political science","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":[0.02884755,0.001066314,0.001158865,0.001876125,0.003747003,0.009451907,0.003233073,0.003103774,0.002579071],"category_scores_gemma":[0.03191133,0.001499981,0.001932451,0.001706185,0.004500872,0.01445293,0.01079608,0.008203181,0.001106431],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003270191,"about_ca_system_score_gemma":0.006102225,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003784569,"about_ca_topic_score_gemma":0.002904572,"domain_scores_codex":[0.9767826,0.01189709,0.002242528,0.001494584,0.006031919,0.001551277],"domain_scores_gemma":[0.9831232,0.008541965,0.002063401,0.003645644,0.001624829,0.001000987],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000472251,0.0005097257,0.002006926,0.0006173257,0.000171747,0.002050678,0.007913711,0.03393982,0.0117801,0.8141007,0.006941802,0.1194953],"study_design_scores_gemma":[0.000515658,0.0001893092,0.0005644052,0.0005556502,0.0001760654,0.001029413,0.001115042,0.4224305,0.03469565,0.4002436,0.1382013,0.0002834328],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01692417,0.0005102297,0.9647182,0.002815614,0.0002005467,0.0005569462,0.00005855441,0.003430516,0.01078519],"genre_scores_gemma":[0.2987657,0.0007359529,0.6925884,0.001086772,0.0001974762,0.0007865087,0.0001900498,0.0005050702,0.005144102],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02884755,"threshold_uncertainty_score":0.1525622,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02866092433976737,"score_gpt":0.3383955874084357,"score_spread":0.3097346630686683,"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."}}