{"id":"W4414567801","doi":"10.1016/j.ifacol.2025.09.103","title":"Leveraging Virtual Commissioning for Digital Twins: An example case","year":2025,"lang":"en","type":"article","venue":"IFAC-PapersOnLine","topic":"Digital Transformation in Industry","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"École de Technologie Supérieure","funders":"Natural Sciences and Engineering Research Council of Canada; Mitacs","keywords":"Reuse; Project commissioning; Shadow (psychology); Virtual reality; Process (computing); Industry 4.0; Visualization","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001006046,0.0002167127,0.000195687,0.0001341163,0.0001703815,0.0002711235,0.000176926,0.0001259307,0.00005744808],"category_scores_gemma":[0.00004409136,0.0002256835,0.00008293588,0.0002208161,0.00003723785,0.001066826,0.000026555,0.0002254942,0.00001887217],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008926285,"about_ca_system_score_gemma":0.00003758847,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002757349,"about_ca_topic_score_gemma":0.00001376126,"domain_scores_codex":[0.9990037,0.000007886604,0.0003263406,0.0002118707,0.0001244881,0.0003256888],"domain_scores_gemma":[0.9993702,0.000162685,0.0000231479,0.0002607476,0.00005255763,0.0001307102],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001110929,0.000435191,0.001322236,0.0007901798,0.0004590847,0.0004484885,0.01013229,0.1611128,0.00428565,0.007886821,0.001211266,0.8118049],"study_design_scores_gemma":[0.005608116,0.0004006616,0.000297883,0.000897848,0.0001291199,0.0009713729,0.03658606,0.7507881,0.008298369,0.001167919,0.1928735,0.00198103],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7678612,0.0001537366,0.1654924,0.0003298832,0.001079101,0.0005635212,0.0004024754,0.00136104,0.06275657],"genre_scores_gemma":[0.9673912,0.000004021126,0.03026092,0.0001893092,0.0001711566,0.00004403519,0.0002659039,0.00004932367,0.001624114],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8098238,"threshold_uncertainty_score":0.9203106,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04085694445711823,"score_gpt":0.2680707725686871,"score_spread":0.2272138281115688,"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."}}