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Repeatable benchmarks for parameterisation methods should be created. This can be split between synthetic and experimental datasets; however, I think we should have varying levels of difficulty / identifiability across the datasets. It's possible that the difficulty level might end up being the division between synthetic and experimental. The high level properties that should be identifiable (and not identifiable) in these datasets:
Thermodynamic properties
Kinetic properties
Transport properties
The text was updated successfully, but these errors were encountered:
Repeatable benchmarks for parameterisation methods should be created. This can be split between synthetic and experimental datasets; however, I think we should have varying levels of difficulty / identifiability across the datasets. It's possible that the difficulty level might end up being the division between synthetic and experimental. The high level properties that should be identifiable (and not identifiable) in these datasets:
The text was updated successfully, but these errors were encountered: