{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000865113,0.0007745037,0.0005887207,0.0005526988,0.0003976649,0.001293056,0.0008462359,0.001260141,0.002420273],"category_scores_gemma":[0.002937061,0.0004079708,0.0003680293,0.001298119,0.0007731793,0.001556354,0.001071464,0.001849234,0.000509332],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001191717,"about_ca_system_score_gemma":0.001047503,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009061411,"about_ca_topic_score_gemma":0.005733146,"domain_scores_codex":[0.9996891,0.0001119534,0.00002013589,0.00006105144,0.00008501582,0.00003281336],"domain_scores_gemma":[0.999361,0.00037928,0.00007807481,0.00003326689,0.000123058,0.00002537119],"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":[0.00004231703,0.00002143433,0.0003332936,0.00006525289,0.00003430466,0.00003481738,0.00002815617,0.9269568,0.0005304969,0.02178445,0.002790663,0.047378],"study_design_scores_gemma":[0.000002747015,0.000006141786,0.00004963556,0.00001010174,0.000003673968,0.000004557033,0.000004019639,0.9849303,0.0001569871,0.0138644,0.000963509,0.00000386486],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01217919,0.007446887,0.9624453,0.003396278,0.0003610648,0.00004515594,0.0001663405,0.0006054002,0.01335435],"genre_scores_gemma":[0.7505369,0.007706624,0.2213299,0.0007663941,0.0007004988,0.0002604536,0.0004352783,0.0001834826,0.01808036],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009061411,"threshold_uncertainty_score":0.01801729,"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."}}