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@@ -6,7 +6,7 @@ This model focuses on shared predictive forecasting using advanced machine learn
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  **Key Idea:** All participants in a supply chain (manufacturers, wholesalers, retailers, and potentially key suppliers) contribute data to a centralized platform. This platform utilizes Transformer-based machine learning models to generate highly accurate demand forecasts. Participants contractually agree to use these forecasts as the primary basis for ordering and production decisions, but within a framework of *structured flexibility* and *shared risk/reward*. This promotes efficiency, reduces waste, optimizes inventory, and mitigates the impact of human unpredictability.
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- The blackbox "inputs" and "outputs" of the model are as follows:
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  ## I. Core Components
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  **Key Idea:** All participants in a supply chain (manufacturers, wholesalers, retailers, and potentially key suppliers) contribute data to a centralized platform. This platform utilizes Transformer-based machine learning models to generate highly accurate demand forecasts. Participants contractually agree to use these forecasts as the primary basis for ordering and production decisions, but within a framework of *structured flexibility* and *shared risk/reward*. This promotes efficiency, reduces waste, optimizes inventory, and mitigates the impact of human unpredictability.
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+ The blackbox "inputs" and "outputs" of the model are listed in the tables in the accompanying Inputs-Outputs.md
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  ## I. Core Components
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