change kahan reference

Author: jalvesz

doc/specs/stdlib_intrinsics.md

@@ -48,7 +48,7 @@ If `dim` is absent, the output is a scalar of the same `type` and `kind` as to t
 
 #### Description
 
-The `stdlib_sum_kahan` function can replace the intrinsic `sum` for `real` or `complex` arrays. It follows a chunked implementation which maximizes vectorization potential complemented by an `elemental` kernel based on the [kahan summation](https://en.wikipedia.org/wiki/Kahan_summation_algorithm) strategy to reduce the round-off error:
+The `stdlib_sum_kahan` function can replace the intrinsic `sum` for `real` or `complex` arrays. It follows a chunked implementation which maximizes vectorization potential complemented by an `elemental` kernel based on the [kahan summation](https://doi.org/10.1145%2F363707.363723) strategy to reduce the round-off error:
 
 ```fortran
 elemental subroutine kahan_kernel_<kind>(a,s,c)
@@ -129,7 +129,7 @@ The output is a scalar of `type` and `kind` same as to that of `x` and `y`.
 
 #### Description
 
-The `stdlib_dot_product_kahan` function can replace the intrinsic `dot_product` for 1D `real` or `complex` arrays. It follows a chunked implementation which maximizes vectorization potential , complemented by the same `elemental` kernel based on the [kahan summation](https://en.wikipedia.org/wiki/Kahan_summation_algorithm) used for `stdlib_sum` to reduce the round-off error.
+The `stdlib_dot_product_kahan` function can replace the intrinsic `dot_product` for 1D `real` or `complex` arrays. It follows a chunked implementation which maximizes vectorization potential , complemented by the same `elemental` kernel based on the [kahan summation](https://doi.org/10.1145%2F363707.363723) used for `stdlib_sum` to reduce the round-off error.
 
 #### Syntax