{"id":"W7128378658","doi":"10.5281/zenodo.18442616","title":"Supply Chain Resilience Metrics: Optimization under Multi-Risk Shocks","year":2025,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Supply Chain Resilience and Risk Management","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Backup; Resilience (materials science); Supply chain; Metric (unit); Pipeline (software); Supply chain management; Service (business); Service provider; Service level","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":[0.006226751,0.001688676,0.001019476,0.001749357,0.0003510967,0.002893697,0.0008460412,0.001174773,0.00155169],"category_scores_gemma":[0.01550058,0.0003463138,0.0008299644,0.00212551,0.001579851,0.003688585,0.002089679,0.00205005,0.0001759005],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002252027,"about_ca_system_score_gemma":0.001365716,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001914689,"about_ca_topic_score_gemma":0.00109533,"domain_scores_codex":[0.9966516,0.001810005,0.0002307347,0.0004344004,0.0006453926,0.0002279605],"domain_scores_gemma":[0.9924435,0.004429538,0.001629495,0.000405177,0.0008046971,0.0002875873],"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":[0.00004758711,0.00003447973,0.003469386,0.0002495032,0.0002009845,0.00006335445,0.00009617535,0.8906134,0.0004552394,0.070958,0.001568666,0.03224318],"study_design_scores_gemma":[0.000008342965,0.0001402974,0.002835585,0.0002031395,0.0000555847,0.00006163559,0.0001567265,0.8096209,0.0006502963,0.1834706,0.002750395,0.00004658483],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07175258,0.005931497,0.9100343,0.002716978,0.0001487954,0.0001476181,0.0006229354,0.000281725,0.008363635],"genre_scores_gemma":[0.9372768,0.002917341,0.05765975,0.0001908998,0.000132136,0.0001755551,0.0004532972,0.00008609387,0.001108063],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006226751,"threshold_uncertainty_score":0.03293061,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02209356179786555,"score_gpt":0.2426004147294136,"score_spread":0.2205068529315481,"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."}}