{"id":"W4392190232","doi":"10.18280/isi.290120","title":"Enhancing Supply Chain Resilience and Efficiency through Fuzzy Logic-based Decision-Making Automation in Volatile Environments","year":2024,"lang":"en","type":"article","venue":"Ingénierie des systèmes d information","topic":"Supply Chain Resilience and Risk Management","field":"Business, Management and Accounting","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Supply chain; Resilience (materials science); Automation; Fuzzy logic; Computer science; Business; Engineering; Artificial intelligence; Marketing; Materials science","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":[0.0007608194,0.0002252627,0.0001910563,0.0007023197,0.0003039491,0.0009321703,0.0002148955,0.00009679041,0.00008936377],"category_scores_gemma":[0.0003064659,0.0001991107,0.0000505913,0.0009337389,0.0001225514,0.007144185,0.0001497055,0.0001404288,0.0002540858],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000232482,"about_ca_system_score_gemma":0.00003798938,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002386135,"about_ca_topic_score_gemma":0.00008691169,"domain_scores_codex":[0.9982333,0.00001745886,0.0006558326,0.0002785741,0.0004438583,0.0003709322],"domain_scores_gemma":[0.9993696,0.000166004,0.0002040532,0.0002101475,0.00003701921,0.00001314477],"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":[0.0001746819,0.0001603173,0.04661971,0.004311932,0.00004085535,0.00008350505,0.01052956,0.1073118,0.001163739,0.07036322,0.001526393,0.7577143],"study_design_scores_gemma":[0.0005825148,0.00004696085,0.06475645,0.002771836,0.00003470972,0.000006991715,0.003724402,0.86486,0.0003060928,0.04964112,0.01269178,0.0005771265],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7136598,0.0006177995,0.2758326,0.0002023802,0.000548323,0.0007393528,0.000004390797,0.000278282,0.008117137],"genre_scores_gemma":[0.9962283,0.00005384365,0.002753944,0.0006908024,0.0001176748,0.00007484385,0.00004266754,0.00001472772,0.00002322898],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7575482,"threshold_uncertainty_score":0.8988939,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00807856649542704,"score_gpt":0.2344136131263519,"score_spread":0.2263350466309249,"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."}}