{"id":"W123459231","doi":"10.20381/ruor-3691","title":"Business Intelligence - Enabled Adaptive Enterprise Architecture","year":2014,"lang":"en","type":"dissertation","venue":"uO Research (University of Ottawa)","topic":"Big Data and Business Intelligence","field":"Business, Management and Accounting","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Business architecture; Enterprise architecture; Computer science; Process management; Business rule; Business intelligence; Knowledge management; Artifact-centric business process model; Business process modeling; Information system; Business Process Model and Notation; Enterprise information system; Business process; Business; Architecture; Engineering; Marketing","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.001105571,0.0004075434,0.0006085086,0.001943166,0.0006243031,0.0002222282,0.002296636,0.0004666117,0.002730998],"category_scores_gemma":[0.0005330277,0.0004479465,0.0002000737,0.002613378,0.0004516464,0.001080116,0.000569884,0.001122403,0.001222221],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009298344,"about_ca_system_score_gemma":0.0002183867,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003129071,"about_ca_topic_score_gemma":0.00901067,"domain_scores_codex":[0.9966592,0.00008033415,0.0003181222,0.0008370131,0.001369445,0.0007359407],"domain_scores_gemma":[0.9956926,0.0002081336,0.0004832153,0.0008039074,0.002759953,0.00005222266],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001441175,0.001494395,0.01544852,0.01463161,0.0007901913,0.0006081625,0.002142791,0.0006250002,0.002697714,0.309252,0.1441782,0.5066902],"study_design_scores_gemma":[0.0004871658,0.00007832046,0.0381152,0.00177367,0.0002109943,0.000004926822,0.007411132,0.002907388,0.0006190211,0.01274597,0.9345046,0.001141661],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.139889,0.0004292465,0.06079121,0.002133522,0.002833399,0.002469809,0.0001833978,0.0004412122,0.7908292],"genre_scores_gemma":[0.910915,0.0005459958,0.001637972,0.0001522984,0.001737396,0.000007621702,0.00352456,0.0001563001,0.08132286],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7903264,"threshold_uncertainty_score":0.9997972,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07085929952772982,"score_gpt":0.3048816991002161,"score_spread":0.2340223995724863,"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."}}