{"id":"W2990797043","doi":"10.1109/edocw.2019.00015","title":"Digital Transformation – Implications for Enterprise Modeling and Analysis","year":2019,"lang":"en","type":"article","venue":"","topic":"Digital Transformation in Industry","field":"Engineering","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Digital transformation; Enterprise modelling; Enterprise integration; Computer science; Enterprise software; Knowledge management; Enterprise information system; Integrated enterprise modeling; Process management; Enterprise systems engineering; Enterprise architecture; Enterprise life cycle; Adaptation (eye); Flexibility (engineering); Stakeholder; Business process; Business transformation; Business process modeling; Business; World Wide Web; Management","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":[0.01531394,0.0008074039,0.001064389,0.006812827,0.002273463,0.01068585,0.002522672,0.002781011,0.00307245],"category_scores_gemma":[0.02085459,0.0005288366,0.001564985,0.009744277,0.009469826,0.0158625,0.004422508,0.003403316,0.0006031595],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006924616,"about_ca_system_score_gemma":0.006406076,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01098926,"about_ca_topic_score_gemma":0.007893373,"domain_scores_codex":[0.9919837,0.005498158,0.0005421138,0.0004460896,0.001205568,0.0003243321],"domain_scores_gemma":[0.9728546,0.0209555,0.001063618,0.002409008,0.002206331,0.0005110603],"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":[0.000006248951,0.00003089356,0.0007852609,0.0002070239,0.00002789263,0.0000979688,0.001953111,0.005141115,0.00007654685,0.9704173,0.002095649,0.01916101],"study_design_scores_gemma":[0.000007228556,0.000009874567,0.0004395805,0.0006287698,0.00001915436,0.0000968951,0.005481961,0.01617277,0.0001989002,0.9131625,0.06376115,0.00002118099],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"review","genre_scores_codex":[0.02940223,0.0380516,0.6351545,0.1298815,0.0008334178,0.000498489,0.0008549758,0.0004895805,0.1648336],"genre_scores_gemma":[0.5826648,0.03290417,0.3664314,0.006131114,0.0004814176,0.0009960051,0.0009994515,0.0002206303,0.009170944],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.01531394,"threshold_uncertainty_score":0.08098882,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01387374851138704,"score_gpt":0.2288264445201494,"score_spread":0.2149526960087624,"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."}}