Follow-up after mean_poisson_deviance array API PR

As a follow-up for #29227.

The following command fails locally:
```
pytest -vl sklearn/metrics/tests/test_common.py -k 'api_regression_metric and mean_poisson_deviance'
```
see full error in https://github.com/scikit-learn/scikit-learn/pull/29227#issuecomment-2244729661

but setting `SCIPY_ARRAY_API=1` works:
```
SCIPY_ARRAY_API=1 pytest -vl sklearn/metrics/tests/test_common.py -k 'api_regression_metric and mean_poisson_deviance'
```

Honestly I think this is fair to say that as a newcomer to the array API work, my feeling is that it can break way too easily in very mysterious ways. There are probably a few unrelated reasons for this but I guess since at the last bi-weekly meetings we agreed that we should try to pay attention to this kind of breakages and improve the situation, here are a few comments on this #29277:
- I think we should have some tests with scipy>=1.14 and `SCIPY_ARRAY_API` unset. This seems something that could easily happen in practice and we should have tests that make sure that nothing breaks. It's not clear to me why only array-api-strict breaks and not pytorch example, maybe as the name implies array-api-strict is even stricter than other namespaces.
- I don't think this is acceptable to skip the test for scipy<1.14 since you know a reasonable user may use `array_api_dispatch=True` with scipy<1.14. To be fair it is not clear to me what happens in this case. I guess scipy will transform the array into a numpy array, and maybe the code afterwards has issues because some arrays are not in the same namespace? Anyway, we should make sure that the user code does not break. If this is really too hard to achieve the alternative is to raise an exception saying something like "to enable array API dispatch with this particular function you need scipy 1.14 and `SCIPY_ARRAY_API=1`".
- the warning about `SCIPY_ARRAY_API` seems too broad (as soon as `set_config(array_api_dispatch=True)` is called?). Could we not have warnings only in a few (at least for now) places where we know we call scipy functions?

_Originally posted by @lesteve in https://github.com/scikit-learn/scikit-learn/issues/29227#issuecomment-2244803503_

COMMENT:
> Did you see the warning when you ran the tests? Or is it lost in a sea of warnings? Asked differently, why did the warning we already have not prevent your negative experience when running the tests?

No I did not see the warnings because there wasn't any, see below for more details why.

I guess as discussed during the meeting, reducing the number of moving pieces would be a great start, so raising an exception when any of the following conditions hold seems probably like a good idea?
- array-API support enabled, scipy<1.14
- array-API support enabled, scipy>=1.14 but `scipy._lib._array_api.SCIPY_ARRAY_API` is `False` (Python variable which is set at import time based on the value of the environment variable `SCIPY_ARRAY_API` see https://github.com/scipy/scipy/blob/9525f45c1cb9068bcb8e02d8fd81abc0c6f4e4ae/scipy/_lib/_array_api.py#L31-L32). Not sure if the env variable is used in other places, but the Python variable is what we should always use I think because that's what is the source of truth to allow Scipy array API support, not the environment variable which can be changed later after scipy has been imported.

Why did I not see any warning?
- it seems like warnings are not shown by default in our pytest setup, we have `--disable-pytest-warnings` in our `setup.cfg` (guess who did that, yours truly, 7+ years ago with a note saying to remove it, I guess it may be about time :sweat_smile:).
- to be honest I may have missed it anyway see screenshot below, it's very easy to get drawn by the red lines and ignore the "warnings summary" part. Here I am only running 4 tests but if I was running the full test suite forget about finding the relevant warning :wink: 
![image](https://github.com/user-attachments/assets/8b2255a0-5cbd-4cf3-8f7d-5cbc91fa9461)

Labels: Array API