{"id":"W3033971127","doi":"10.1109/access.2020.2998723","title":"Digital Twin for the Oil and Gas Industry: Overview, Research Trends, Opportunities, and Challenges","year":2020,"lang":"en","type":"article","venue":"IEEE Access","topic":"Digital Transformation in Industry","field":"Engineering","cited_by":357,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; Memorial University of Newfoundland","funders":"Memorial University of Newfoundland; Atlantic Canada Opportunities Agency; Mitacs; University of Toronto; Petroleum Research Newfoundland and Labrador","keywords":"Fossil fuel; Petroleum industry; Computer science; Data science; Environmental science; Engineering; Waste management","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.004012261,0.0008877457,0.00102535,0.01982091,0.001250755,0.007485596,0.001033538,0.002674721,0.005610803],"category_scores_gemma":[0.009242365,0.0005703277,0.001186004,0.02734961,0.001590242,0.01006653,0.002291577,0.002028954,0.001622551],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003198247,"about_ca_system_score_gemma":0.01013408,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005698727,"about_ca_topic_score_gemma":0.007379069,"domain_scores_codex":[0.9979385,0.0004577043,0.0003836218,0.0002850683,0.000750055,0.0001849712],"domain_scores_gemma":[0.9864985,0.009042302,0.001101621,0.0002068626,0.002655765,0.0004949254],"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":[0.00007353282,0.00008991499,0.002269858,0.06735249,0.0001233455,0.0005512956,0.001845406,0.0005052148,0.001162442,0.05119227,0.02566288,0.8491713],"study_design_scores_gemma":[0.00001238968,0.0001546794,0.007029642,0.08252016,0.000444706,0.001616306,0.005445372,0.0005516137,0.001123293,0.01431569,0.8867072,0.00007909146],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.001642438,0.9847695,0.000884984,0.003510079,0.0004545604,0.0000354357,0.0001349956,0.00002891177,0.008539191],"genre_scores_gemma":[0.00683899,0.9899364,0.00125728,0.0006833879,0.0002952409,0.0000280862,0.0001411013,0.00001037277,0.0008091618],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.01982091,"threshold_uncertainty_score":0.02320504,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4065423539478378,"score_gpt":0.3655984489252738,"score_spread":0.04094390502256401,"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."}}