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docs: add pred_wait explanation for pred_saturation field

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@@ -82,7 +82,7 @@ Task (must complete):
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  Mainly based on prediction.phase_waits pred_saturation (already calculated), output the final green light time for each phase in the next cycle (unit: seconds), while satisfying hard constraints.'
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  ```
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- **Input format**: JSON wrapped in `【cycle_predict_input_json】...【/cycle_predict_input_json】` tags, containing `prediction.phase_waits` — an array of per-phase objects with `phase_id`, `pred_saturation`, `min_green`, `max_green`, and `capacity`.
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  **Output format**: A JSON array of objects `[{"phase_id": <int>, "final": <int>}, ...]`, where `final` is the allocated green time in integer seconds for each phase.
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  Mainly based on prediction.phase_waits pred_saturation (already calculated), output the final green light time for each phase in the next cycle (unit: seconds), while satisfying hard constraints.'
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  ```
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+ **Input format**: JSON wrapped in `【cycle_predict_input_json】...【/cycle_predict_input_json】` tags, containing `prediction.phase_waits` — an array of per-phase objects with `phase_id`, `pred_saturation`, `min_green`, `max_green`, and `capacity`. Here `pred_saturation = pred_wait / capacity`, where `pred_wait` is the predicted number of waiting vehicles for this phase in the next cycle, which can be computed using time-series forecasting models such as [LightGBM](https://github.com/microsoft/LightGBM) based on historical traffic data.
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  **Output format**: A JSON array of objects `[{"phase_id": <int>, "final": <int>}, ...]`, where `final` is the allocated green time in integer seconds for each phase.
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