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At high doses the additivity model underpredicted the empirical effects by 2- to 3-fold.
At high doses the dose-additivity model underpredicted the empirical effects by 2- to 3-fold but worked well at lower doses typical of environmental exposures.
There was no deviation from dose additivity at the lowest tested doses of the mixture, but at higher test doses the additivity model underpredicted the empirical effects by a factor of 2 3.
The model underpredicted the observed mean SBP by ~2.1 mmHg and considerably underpredicted the expected proportion of current smokers at the end of the simulation period (2% of the whole cohort) (Supplementary Fig. 5).
Initial compound file validation against clinical data showed that in the absence of detailed information on the supersaturation state following stomach emptying to intestine and the gut wall permeability, the model underpredicted the drug absorption and the elimination profile (data not shown).
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Whereas, RSM and standard k ε model underpredict the turbulent kinetic energy profiles significantly in the impeller region.
We found that both models underpredicted the observations.
For example in fuels with low levels of H2, both models underpredict the measurements.
Using ClO4− inhibition of dietary iodide uptake into the thyroid, the model underpredicted both the rapid decrease in serum TT4 concentrations and the rise in serum TSH concentrations.
We found that the model underpredicted most of the cases except for two in which CPF residue was detected in the 24-hr duplicate food samples.
The Gamma Log model underpredicted substantially in the first nine deciles (values ranging from 0.33 to 0.66) and overpredicted in the top decile (2.04) with BCIs that also never included 1.0.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com