{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004938163,0.0008103985,0.0006244146,0.007886439,0.001577371,0.009939237,0.002274608,0.002284081,0.002567632],"category_scores_gemma":[0.005965433,0.0005099018,0.001062483,0.0112753,0.01647617,0.008502149,0.003144885,0.002415128,0.00036636],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005711778,"about_ca_system_score_gemma":0.006157703,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003695057,"about_ca_topic_score_gemma":0.003622176,"domain_scores_codex":[0.9966031,0.00232493,0.0001458272,0.0002919894,0.0004375045,0.0001965804],"domain_scores_gemma":[0.9932367,0.005299146,0.0004319178,0.0005619458,0.0003105198,0.0001597038],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.000006943544,0.00001419783,0.0006309039,0.0004444509,0.00002797803,0.00008764469,0.002246581,0.004564521,0.0001625319,0.9781483,0.0003414467,0.01332442],"study_design_scores_gemma":[0.00001593778,0.00004331851,0.0007164571,0.001377333,0.00007221531,0.0003140333,0.006370297,0.01480513,0.000478414,0.9148657,0.06091019,0.00003105844],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0483951,0.06494326,0.5948159,0.02158526,0.000353809,0.0004041335,0.0003167117,0.0003408865,0.2688449],"genre_scores_gemma":[0.8498643,0.02675736,0.1171367,0.001696577,0.0001477986,0.0005343166,0.000224091,0.0000712554,0.003567499],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009939237,"threshold_uncertainty_score":0.04144204,"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."}}