{"id":"W4416420387","doi":"10.1016/j.clscn.2025.100287","title":"Leveraging digital twins for enhanced sustainable warehouse management","year":2025,"lang":"en","type":"article","venue":"Cleaner Logistics and Supply Chain","topic":"Digital Transformation in Industry","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Data warehouse; Sustainability; Carbon footprint; Warehouse; Greenhouse gas; Management accounting; Aggregate (composite); Cost accounting; Accounting information system","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":[0.001281374,0.0006025089,0.0003746157,0.000897062,0.0004638075,0.003443946,0.00111942,0.000684188,0.002710199],"category_scores_gemma":[0.0026467,0.0003414045,0.0007848828,0.001348216,0.0007578171,0.005501319,0.003236974,0.0009355275,0.0004981463],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001273898,"about_ca_system_score_gemma":0.001552273,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007658467,"about_ca_topic_score_gemma":0.007384833,"domain_scores_codex":[0.9993981,0.0002135292,0.00004206156,0.0001089732,0.0001578563,0.00007951999],"domain_scores_gemma":[0.9992543,0.000239336,0.00008327491,0.0002068357,0.0001348806,0.00008135446],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001691423,0.0001564753,0.009113157,0.0001010563,0.00006501105,0.0003650363,0.0003919789,0.8302941,0.006105642,0.0764976,0.00137203,0.07536867],"study_design_scores_gemma":[0.0000109147,0.00007177736,0.0007869188,0.0000242248,0.00002377622,0.00007132862,0.0002254496,0.9624817,0.004647597,0.02199439,0.009635138,0.00002688564],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1558694,0.0002529347,0.8218062,0.0007559891,0.0001048718,0.0001582451,0.0005817141,0.001640322,0.01883019],"genre_scores_gemma":[0.8329303,0.0003719838,0.1627878,0.00008286667,0.0000174595,0.00007079956,0.0006433083,0.0001471062,0.002948439],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007658467,"threshold_uncertainty_score":0.01522779,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01181255537640173,"score_gpt":0.2196128985249041,"score_spread":0.2078003431485023,"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."}}