{"id":"W7083576528","doi":"10.1016/j.ifacol.2025.09.249","title":"Generative AI in Supply Chain Resource Orchestration: A Conceptual Perspective","year":2025,"lang":"en","type":"article","venue":"IFAC-PapersOnLine","topic":"Geochemistry and Geologic Mapping","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Orchestration; Enabling; Supply chain; Resource (disambiguation); Relevance (law); Supply chain management; Resource management (computing); Competitive advantage; Dynamic capabilities","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002774387,0.0001903516,0.000221362,0.00009601611,0.0001315962,0.00008034703,0.0005582156,0.0001292545,0.00008627783],"category_scores_gemma":[0.0003026259,0.0001810665,0.00006441875,0.0006275077,0.0001661737,0.0001970367,0.0001842954,0.0003512014,0.00001923126],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001343001,"about_ca_system_score_gemma":0.0002319434,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009218881,"about_ca_topic_score_gemma":0.0001041693,"domain_scores_codex":[0.9985594,0.0001248315,0.0002420754,0.0005727363,0.000175392,0.0003255762],"domain_scores_gemma":[0.999181,0.0001434526,0.00006111801,0.0003788626,0.000170331,0.00006518771],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001009699,0.0005182998,0.004216682,0.00005736308,0.0001206372,0.0003166197,0.04048999,0.00484614,0.03121161,0.9074623,0.001948782,0.008710587],"study_design_scores_gemma":[0.009044392,0.0009282253,0.03288328,0.0007086694,0.00006414608,0.0001624581,0.07916439,0.526852,0.06363931,0.08540568,0.1982856,0.002861842],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.1003756,0.001760998,0.1431271,0.4811931,0.0007224948,0.001035114,0.00003642832,0.0005725338,0.2711767],"genre_scores_gemma":[0.7640395,0.00001825298,0.2002335,0.01009157,0.0003795817,0.00007039288,0.00004317404,0.000005319755,0.02511871],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8220567,"threshold_uncertainty_score":0.7383677,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01416216860379624,"score_gpt":0.2640752280110821,"score_spread":0.2499130594072859,"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."}}