[jharlow-intel]

Adds ci/ and .github/workflows/intel-ci.yml, which build the conda packages and the wheels for Linux and Windows, on every declared Python, and test each in a clean environment. The recipe skips macOS, as conda-forge/mkl_umath-feedstock does.

• conda-recipe/ is now the only recipe: the conda-forge one that was conda-recipe-cf/. The Intel-channel recipe and conda-package.yml are removed; conda-package-cf.yml builds conda-recipe/ and keeps its check names.
• The conda packages build Python 3.10 to 3.15 plus 3.14t, from the python: list in conda_build_config.yaml. The wheels follow the pyproject.toml classifiers: 3.10 to 3.15 plus 3.14t and 3.15t.
• Wheels build with cibuildwheel and icx: on Linux from Intel's oneAPI yum repository, on Windows from conda-forge's dpcpp_win-64, which ci/install_icx.py installs. They leave MKL and the compiler runtime out and require mkl, intel-openmp and intel-cmplr-lib-rt >=2026.2,<2027 through [tool.gh-ci] wheel-requires, which ci/build.py adds to each wheel.
• meson.build adds Library to CMake's search path on Windows, where mkl-devel puts its CMake config.
• ci/test.py runs pytest --pyargs mkl_umath on the installed package.
• ci/benchmark.py runs the asv suite in benchmarks/ against the installed package: one quick sample of each benchmark on a pull request, a full measurement on a tag.

Miniforge is pinned to 26.7.2-0, as 26.9.4-0 makes setup-miniconda's conda init fail on Windows runners.

Validation: run 42099116172 built and tested the conda packages and the wheels for 3.10 and 3.15 on Linux and Windows; all 17 jobs passed. Not run yet: the full matrix, which only main and tags build.