{"id":"W2168204271","doi":"10.1109/scc.2007.137","title":"WS-Policy4MASC - A WS-Policy Extension Used in the MASC Middleware","year":2007,"lang":"en","type":"article","venue":"","topic":"Service-Oriented Architecture and Web Services","field":"Computer Science","cited_by":36,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Computer science; XML; Middleware (distributed applications); Set (abstract data type); Extension (predicate logic); Adaptation (eye); Web service; Control (management); Action (physics); Programming language; Process management; Distributed computing; World Wide Web; 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":[0.006193697,0.001149297,0.0008630648,0.001315142,0.001237247,0.003075012,0.002315494,0.00187109,0.005150526],"category_scores_gemma":[0.008067763,0.001121774,0.001380441,0.001509785,0.001026636,0.003550629,0.001727275,0.002763547,0.004343547],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001854958,"about_ca_system_score_gemma":0.003849064,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007271206,"about_ca_topic_score_gemma":0.004398979,"domain_scores_codex":[0.996617,0.0006983022,0.0005593855,0.000357239,0.0014633,0.0003048359],"domain_scores_gemma":[0.9950922,0.0009474118,0.0005362768,0.001842838,0.001354846,0.0002265085],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001636612,0.0008932309,0.005708857,0.001636838,0.0003983124,0.002902684,0.001984137,0.06970819,0.09927613,0.4402973,0.1036221,0.2719357],"study_design_scores_gemma":[0.0001354059,0.0001211677,0.0009915539,0.0001942981,0.0001193356,0.0008580947,0.00008274688,0.203721,0.09115699,0.02115665,0.6812821,0.0001807203],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01420148,0.0003031351,0.9064909,0.0005916485,0.0004971186,0.001231019,0.002883195,0.05470498,0.01909658],"genre_scores_gemma":[0.1265686,0.0008420981,0.8151772,0.001193664,0.0002363977,0.001817867,0.009349461,0.008955633,0.03585907],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.007271206,"threshold_uncertainty_score":0.03275579,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01670624454087668,"score_gpt":0.2753243350583914,"score_spread":0.2586180905175147,"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."}}