{"id":"W4287218188","doi":"10.5539/cis.v15n3p37","title":"Integration of AI Supported Risk Management in ERP Implementation","year":2022,"lang":"en","type":"article","venue":"Computer and Information Science","topic":"ERP Systems Implementation and Impact","field":"Business, Management and Accounting","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Bulgarian National Science Fund","keywords":"Computer science; Risk management; Process (computing); Risk analysis (engineering); Risk assessment; Process management; Risk management plan; Knowledge management; Business intelligence; Business process; IT risk management; Operations management; Work in process; Business; Computer security","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":[0.01349005,0.000703255,0.0004250511,0.003377471,0.001103047,0.007785828,0.001919703,0.001773237,0.003644438],"category_scores_gemma":[0.02753257,0.0005727043,0.0006397378,0.001928329,0.001627458,0.006175295,0.004021527,0.002162746,0.001023782],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002571893,"about_ca_system_score_gemma":0.004917855,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001624266,"about_ca_topic_score_gemma":0.001289167,"domain_scores_codex":[0.9814683,0.010572,0.001234201,0.0008573818,0.005083498,0.0007844459],"domain_scores_gemma":[0.9786372,0.01206205,0.002042722,0.002168283,0.004332006,0.0007576423],"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":[0.0001582791,0.0007842506,0.009162386,0.0009690461,0.000208999,0.0006686556,0.00813703,0.0274471,0.004879464,0.1626375,0.003034407,0.7819129],"study_design_scores_gemma":[0.0001770046,0.001945495,0.02551435,0.003553297,0.0003912338,0.002009073,0.01497816,0.3049365,0.01799456,0.4068425,0.2211586,0.0004992588],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09500272,0.003992085,0.7385269,0.01489258,0.0004275086,0.0008468886,0.00009499371,0.002042601,0.1441738],"genre_scores_gemma":[0.6625362,0.001896647,0.3260798,0.0005829508,0.0001795599,0.0003775049,0.0001195962,0.0001320829,0.008095756],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01349005,"threshold_uncertainty_score":0.07134306,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01851849755958309,"score_gpt":0.3033133238485283,"score_spread":0.2847948262889452,"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."}}