{"id":"W2148428941","doi":"10.1109/edoc.2007.18","title":"Business Process Integration by Using General Rule Markup Language","year":2007,"lang":"en","type":"article","venue":"","topic":"Business Process Modeling and Analysis","field":"Business, Management and Accounting","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Athabasca University; Simon Fraser University","funders":"","keywords":"Business rule; RuleML; Computer science; Markup language; Artifact-centric business process model; Business process modeling; Semantics of Business Vocabulary and Business Rules; Business domain; Business process; Process management; Business Process Model and Notation; Business process discovery; Leverage (statistics); Software engineering; XML; World Wide Web; Business; Artificial intelligence; XHTML; Work in process; Marketing","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":[],"consensus_categories":[],"category_scores_codex":[0.0005013376,0.0002395471,0.0002355201,0.0003561907,0.0002390979,0.0003879364,0.000239776,0.0001049563,0.0003321973],"category_scores_gemma":[0.00008947157,0.0001989563,0.00007040638,0.001581993,0.00004108358,0.001503439,0.00006637984,0.0001235312,0.00008692489],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000336075,"about_ca_system_score_gemma":0.00002554154,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002898088,"about_ca_topic_score_gemma":0.0002036518,"domain_scores_codex":[0.9985451,0.000003802391,0.0003601536,0.0003625159,0.0003364616,0.0003920282],"domain_scores_gemma":[0.9989607,0.0000123985,0.000198857,0.000198952,0.0006112297,0.00001789217],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004204114,0.001222726,0.05045293,0.002059678,0.0002963973,0.0001132766,0.0007285831,0.01596469,0.2244051,0.006442601,0.01656078,0.6813329],"study_design_scores_gemma":[0.001758838,0.000006585874,0.006345501,0.000292487,0.0005366353,0.00001639647,0.004285571,0.9572875,0.01747435,0.003709974,0.006304433,0.001981732],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8159056,0.0001675839,0.1722769,0.0003467207,0.0001847059,0.00009008194,0.000001778831,0.0002581933,0.01076837],"genre_scores_gemma":[0.9940973,0.000004999299,0.001293202,0.001505381,0.001271839,0.000005166644,0.0001531727,0.00004237061,0.001626558],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9413228,"threshold_uncertainty_score":0.8113204,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01349592121465099,"score_gpt":0.2597580774123783,"score_spread":0.2462621561977273,"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."}}