Overview of the collection
At 2018/01/01, when the collection had 1000 entries, there were 112 zero-variate data types, and 153 univariate data types, in 588 combinations, written by 125 authors. So, few entries share the same data type combination and the number of data types is very much larger than the number of parameters. This argues for comparison on the basis of parameters, since all parameters were estimated for all species. Moreover, by being mechanistic (= based on first principles), DEB models interprete data, rather than just describe it, so can reveal inconsistencies in data and predict un-measured properties of species as functions of parameters.
Apart from extant species, the collection also has a number of extinct ones, demonstrating that DEB models can still be applied if data availability is poor. Examples are: Deinosuchus, Pterodaustro, Tyrannosaurus, Archaeopteryx and great auk. Needless to say, however: more data generally reduces uncertainty in parameter values.
Data completeness and mean relative errors
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The entries continue to change as the collection grows for several reasons: errors are spotted and corrected; more data is included; assumptions about data quality change; entries are split up by population; our understanding of what are the best priors to use for particular taxa increases; algorithms for estimation are improved; the model changed.
Add-my-pet makes explicit a number of wide spread scientific problems such as: data quality, differences between experiments etc. The resulting parameter estimates depend on a lot of assumptions concerning which data we choose to include and exclude as well as how the data is interpreted (e.g. what we are willing to assume about the initial conditions of the organism.)