Abstracting model prior and family for hierarchical ODE in U34

Goal: abstract U34 in [this](https://github.com/hyunjimoon/DataInDM/blob/main/Digest_Day/2%20Bayesian%20Calibration.md#user-program-wf-one-actor-and-its-tool) table to the highest level

1. How often does the measurement model (`family`) change? Can all (or some) changes be covered with prior change (e.g. adding hierarchy; family `poisson` to `neg_binom` is the same with gamma prior for rate)?

2. What scenarios does user decide to change prior distribution (not prior parameter)?

3. Could you give some feedback on the following prior type classification (details [here](https://github.com/hyunjimoon/DataInDM/blob/main/Digest_Day/2%20Bayesian%20Calibration.md#what-probability-measure-and-pooler))?

4. Confused about brms family `quas`
```
quasi(link = "identity", variance = "constant")
quasibinomial(link = "logit")
quasipoisson(link = "log")
```