{"id":"W3037834279","doi":"10.5430/rwe.v11n3p311","title":"Improving the Efficiency of an Industrial Enterprise Due to the Architectural Approach to a Complex Information Management System","year":2020,"lang":"en","type":"article","venue":"Research in World Economy","topic":"Economic and Technological Systems Analysis","field":"Business, Management and Accounting","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Productivity; Production (economics); Quality (philosophy); Business; Architecture; Enterprise information system; Enterprise architecture; Information system; Process management; Industrial organization; Computer science; Engineering management; Knowledge management; Engineering; Economics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001606364,0.0004020908,0.0002349821,0.001526316,0.0008058536,0.005878636,0.0005363636,0.0005912889,0.002211804],"category_scores_gemma":[0.003805364,0.0002251773,0.0002447358,0.001966081,0.00180378,0.003786537,0.00151452,0.000633625,0.0008681295],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001344193,"about_ca_system_score_gemma":0.002478618,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001600347,"about_ca_topic_score_gemma":0.001459091,"domain_scores_codex":[0.9980551,0.0006691492,0.0001247291,0.0001538265,0.0008619725,0.0001352744],"domain_scores_gemma":[0.9984092,0.0005611166,0.0001745218,0.0003980675,0.0003571957,0.00009997467],"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":[0.00007362042,0.0001648974,0.009308401,0.0005206898,0.00009910887,0.0002271967,0.00245968,0.03736946,0.01782594,0.5752515,0.008390915,0.3483086],"study_design_scores_gemma":[0.00008498105,0.000335446,0.03251853,0.0005621363,0.0002060209,0.0007123218,0.002337799,0.1418786,0.01225967,0.4832185,0.3257554,0.0001305912],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2148651,0.004702168,0.5211591,0.008779019,0.0001423703,0.0002855754,0.0001707943,0.001686728,0.2482092],"genre_scores_gemma":[0.8203468,0.003306355,0.1646006,0.0003977978,0.000130526,0.000110717,0.0001739498,0.0001619091,0.01077139],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005878636,"threshold_uncertainty_score":0.00975281,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08305246384316008,"score_gpt":0.2614448884441358,"score_spread":0.1783924246009758,"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."}}