Dilan Pathirana

Could you try optimizing the parameters on `log10` scale? e.g. simply specify this in the PEtab parameters table. It appears to resolve many instances of the issues.

Nice! Yes, may just be an issue of nonidentifiability due to the data, i.e. if you were to do practical identifiability analysis (e.g. naively with profile likelihoods or MCMC sampling...

This is currently being develop separately [1], and will hopefully be integrated into the next PEtab version. Documentation is currently poor but there is a brief example [2] that involves...

I would also suggest Euclidean distance and, independently of this issue, that $\mathrm{rtol}$ and $\mathrm{atol}$ are checked independently, e.g. for Euclidean distance: $$ \sqrt{\sum_i \dot x^2_i} < \mathrm{rtol} \times \sqrt{\sum_i...

> @dilpath just had a look at this as it would be helpful in #1996. In the current implementation, gradients are wrong because `simulate_petab` now applies scaling, but this transformation...

The current status is that the test for each benchmark model needs to be made to pass, e.g. by finding a vector for each model that reliably passes the gradient...

Is there a downside to coupling it to PEtab? The upcoming PEtab Result format could cover ensemble predictions as simulation experiments. This could reduce and shift this part > to...

> What is generated from a parameter ensemble or model ensemble? I'd be happy to hear more about the use cases for a model ensemble first. If it's the calibrated...

> Looking at it, I feel like the PredictionResult as a light wrapper is perfectly fine as is, one might be able to condense it by just having this as...

Line numbers were added in #467 after a couple of people had issues with whitespace-only lines being added to the end of their PEtab TSV files (possibly after exporting from...