diff --git a/src/scores/continuous/standard_impl.py b/src/scores/continuous/standard_impl.py
index 44deab96..47fe08b9 100644
--- a/src/scores/continuous/standard_impl.py
+++ b/src/scores/continuous/standard_impl.py
@@ -354,14 +354,13 @@ def pbias(
     """
     Calculates the percent bias, which is the ratio of the additive bias to the mean observed value, multiplied by 100.
 
-    Percent bias is used for evaluating and comparing forecast accuracy across stations or dataset with varying magnitudes.
-    By expressing the error as a percentage of the observed value, it allows for standardized comparisons, enabling assessment
-    of forecast performance regardless of the absolute scale of values. Like multiplicative_bias, Percent bias will return a np.inf
-    where the mean of `obs` across the dims to be reduced is 0.
-    It is defined as
+    Percent bias is used for evaluating and comparing forecast accuracy across stations or datasets with varying magnitudes.
+    By expressing the error as a percentage of the observed value, it allows for standardised comparisons, enabling assessment
+    of forecast performance regardless of the absolute scale of values. Like :py:func:`scores.continuous.multiplicative_bias`,
+    ``pbias`` will return a ``np.inf`` where the mean of ``obs`` across the dims to be reduced is 0. It is defined as
 
     .. math::
-        \\text{Percent bias} = 100 * \\frac{\\sum_{i=1}^{N}(x_i - y_i)}{\\sum_{i=1}^{N} y_i}
+        \\text{Percent bias} = 100 \\cdot \\frac{\\sum_{i=1}^{N}(x_i - y_i)}{\\sum_{i=1}^{N} y_i}
 
     where:
         - :math:`x_i` = the values of x in a sample (i.e. forecast values)
@@ -373,9 +372,9 @@ def pbias(
         fcst: Forecast or predicted variables.
         obs: Observed variables.
         reduce_dims: Optionally specify which dimensions to reduce when
-            calculating the percentage additive bias. All other dimensions will be preserved.
+            calculating the percent bias. All other dimensions will be preserved.
         preserve_dims: Optionally specify which dimensions to preserve when
-            calculating the additive bias percentage. All other dimensions will be reduced. As a
+            calculating the percent bias. All other dimensions will be reduced. As a
             special case, 'all' will allow all dimensions to be preserved. In
             this case, the result will be in the same shape/dimensionality
             as the forecast, and the errors will be the error at each
@@ -393,7 +392,7 @@ def pbias(
             Water Resources Research, 29(4), 1185-1194. https://doi.org/10.1029/92WR02617
         -   Alfieri, L., Pappenberger, F., Wetterhall, F., Haiden, T., Richardson, D., & Salamon, P. (2014).
             Evaluation of ensemble streamflow predictions in Europe. Journal of Hydrology, 517, 913-922.
-            http://dx.doi.org/10.1016/j.jhydrol.2014.06.035
+            http://doi.org/10.1016/j.jhydrol.2014.06.035
         -   Dawson, C. W., Abrahart, R. J., & See, L. M. (2007). HydroTest:
             A web-based toolbox of evaluation metrics for the standardised assessment of hydrological forecasts.
             Environmental Modelling and Software, 22(7), 1034-1052.