docs: auto-update documentation for v4.3.1

docs/source/user_guide/concepts/models.rst

@@ -205,3 +205,4 @@ Most users start with Presets and only drop down to lower levels when they need
 custom behavior. The component boundaries are designed so you can replace one piece
 (e.g., swap a Forecaster or add a Transform) without rewriting the rest of the
 pipeline.
+```

docs/source/user_guide/guides/probabilistic_forecasting.rst

@@ -134,6 +134,8 @@ maintain consistency between levels.
      - ``reg:quantileerror`` objective
      - Fast iteration on linear-tractable problems, or as a robust baseline.
      - Uses XGBoost's built-in quantile regression for linear boosters.
+       Quantile levels are sorted internally before training, so input order
+       does not matter.
    * - **LightGBM**
      - ``MultiQuantileRegressor``
      - Large feature sets where LightGBM's training speed pays off.
@@ -263,4 +265,5 @@ See :doc:`/user_guide/guides/backtesting_tutorial` for how to evaluate forecast
    - :doc:`/user_guide/guides/forecasting` for the overall forecasting workflow (fitting, predicting, model selection).
    - :doc:`/user_guide/concepts/models` for understanding how different model types compare.
    - :doc:`/user_guide/guides/backtesting_tutorial` for evaluating forecast performance systematically.
-   - :doc:`/user_guide/guides/reliability_fallback` for operational concerns like fallback behavior when data is missing.
+   - :doc:`/user_guide/guides/reliability_fallback` for operational concerns like fallback behavior when data is missing.
+```