{"id":"W7143973027","doi":"10.71465/ajainn621","title":"AI in Logistics: Neural Networks for Optimized Supply Chain Management","year":2023,"lang":"","type":"article","venue":"American Journal of Artificial Intelligence and Neural Networks","topic":"Supply Chain Resilience and Risk Management","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Supply chain; Artificial neural network; Supply chain management; Service management; Supply chain risk management; Demand forecasting","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.002364895,0.0007580253,0.001364825,0.001595665,0.0005142515,0.0009944418,0.001042693,0.0001829017,0.0001014341],"category_scores_gemma":[0.0001583901,0.0006778181,0.0005285264,0.003685858,0.001028252,0.001184697,0.0005890706,0.001015657,0.00001985983],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008868089,"about_ca_system_score_gemma":0.00002725771,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002719939,"about_ca_topic_score_gemma":0.0001421218,"domain_scores_codex":[0.9941995,0.0001533323,0.002447886,0.0008513645,0.0006516597,0.001696321],"domain_scores_gemma":[0.9965749,0.0007154388,0.001709727,0.0004226611,0.0004125634,0.0001647566],"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":[0.00129037,0.0001377682,0.001339043,0.00009383986,0.0001184036,0.0003635559,0.0001153157,0.5729684,0.000002298167,0.002088328,0.002251372,0.4192314],"study_design_scores_gemma":[0.0004545753,0.0007469967,0.001186308,0.0003457896,0.0003535093,0.00002071973,0.009213611,0.9817343,0.000006948784,0.003262087,0.00196464,0.0007104591],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1533875,0.004748346,0.8038893,0.02403521,0.00988852,0.00363236,0.00001413113,0.0001788848,0.0002257954],"genre_scores_gemma":[0.9799509,0.009886209,0.0005620386,0.005558965,0.003708825,0.0000609269,0.00003086632,0.00009197702,0.0001493143],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8265634,"threshold_uncertainty_score":0.9995673,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03121343137341633,"score_gpt":0.28834258964905,"score_spread":0.2571291582756337,"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."}}