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GP models were interpreted on the basis of ligand descriptors.
Gas tracer responses in cold flow models were interpreted by a one-dimensional axial dispersion model, and combined with reaction kinetics to develop a conversion model.
The maps and model rules resulting from the multiple factor models were interpreted to be more precise depictions of a particular species habitat when compared with the models that used vegetation type only.
Only those PCs that were statistically significantly correlated to RSA data or included in the multivariate models were interpreted.
Significant interactions between a prognostic factor and country in these models were interpreted as this factor having different associations with outcome in the countries.
The coefficients in these models were interpreted as either log odds (OR) in binary GLM models or multiplicative factors (MF) in Poisson GLM models.
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These models are interpreted in terms of a biological drive for cognition.
Note that whereas propositions in modular models are interpreted semantically, as truth values, justifications are interpreted syntactically, as sets of formulas.
This article identifies measures to ensure that enterprise models are interpreted as intended, thereby controlling the quality of processes using and reusing enterprise models.
Examples are employed where the resulting terrain models are interpreted with additional field inspection to further the understanding of the archaeological features and structures.
The discontinuities between the two models are interpreted in terms of differences in the composition of the neutral atmosphere in the two latitude regions.
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