{"id":"W4406851005","doi":"10.1002/cjce.25611","title":"Digital twins: Transforming the chemical process industry—A review","year":2025,"lang":"en","type":"article","venue":"The Canadian Journal of Chemical Engineering","topic":"Digital Transformation in Industry","field":"Engineering","cited_by":27,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Process (computing); Business; Process management; Process engineering; Computer science; Engineering","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002298331,0.0001833125,0.0002378309,0.0001024436,0.00005278233,0.000168992,0.000646195,0.0001924653,0.00003187038],"category_scores_gemma":[0.0002151827,0.0001217385,0.0001358616,0.0005220586,0.0000869938,0.0004379337,0.000007024438,0.001454158,0.000004565457],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002229418,"about_ca_system_score_gemma":0.0003267983,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001041995,"about_ca_topic_score_gemma":0.00000486451,"domain_scores_codex":[0.998847,0.00000434658,0.0005256488,0.00006641776,0.0002135802,0.0003429857],"domain_scores_gemma":[0.9993237,0.0001024019,0.00004263814,0.0001732165,0.00009872482,0.0002592633],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00006169884,0.0001088156,0.0007758329,0.02043524,0.002940549,0.0003133817,0.005510627,0.5005853,0.04551477,0.02538816,0.09568521,0.3026804],"study_design_scores_gemma":[0.001942889,0.00004875839,0.00006906936,0.02610428,0.0005791294,0.00205281,0.0005502903,0.02527445,0.5212228,0.002269777,0.418078,0.001807714],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6709151,0.043111,0.007904329,0.02691706,0.003592083,0.001830131,0.0001618532,0.0005641594,0.2450043],"genre_scores_gemma":[0.9993752,0.0000347454,0.00002642378,0.0003282173,0.0001483326,0.00001089512,0.000002802117,0.00002531414,0.00004808675],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4757081,"threshold_uncertainty_score":0.6317675,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009574070031719043,"score_gpt":0.2111725112275862,"score_spread":0.2015984411958671,"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."}}