Revisit Multi-Output Support Naming Conventions

Two new multi-output input types are being added and the PR sparked some debate/discussion surrounding their names and the wider spread naming conventions that have been adopted in KernelFuntions. The main thread discussing these can be found [here].(https://github.com/JuliaGaussianProcesses/KernelFunctions.jl/pull/310#discussion_r661490968).

Some starting points:

• MO vs MultiOutput. Concise or explicit?
• Do we like the prefix isotopic? Is it too jargony?

Quote from paper linked above:
In the geostatistics literature, if each output has the same set of inputs the model
is called isotopic

Pros:
It has a specific meaning in this context, clearly identifying what it is
Cons:
Might scare users off, lengthens names

• Relating to the PR linked above, how do we make these accessible? Less "wordy" helpers? What do we call those?
• Should composite type field names have more descriptive names?
  eg. kernels, mokernel and weights instead of g, e and A for the slfm
• the LinearMixingModelKernel is a kernel, not a model. Maybe it should be renamed LinearMixingKernel for eg. I think we've all agreed on this already.

Start by reading the discussion in PR #310 and the linked thread, then inspect src/mokernels/slfm.jl, especially the composite type fields. The work is complete when the project has a documented, agreed naming convention for multi-output types, helpers, fields, and LinearMixingModelKernel.