Include objective function values and gradients at nominal parameter values

[dweindl]

As mentioned in https://github.com/Benchmarking-Initiative/Benchmark-Models-PEtab/issues/208, I think the relevance of this repository could be increased further, by including objective function values and gradients at the provided nominal parameter values, supporting its use a PEtab integration test suite.

I would like to include:

• the likelihood (potentially for each individual simulation condition + total)
• the prior
• the unnormalized posterior
• the respective gradients
• ...?

The specific format is to be discussed. I'd suggest using some easily extendable json/yaml file in each problem directory.

I could provide the results from pypesto/amici. Would somebody be willing to do the same using another tool for validation?