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Uncertainty in model parameters was quantified using confidence intervals obtained through bootstrapping the data, and uncertainty in model outputs such as the predicted degree distribution was quantified using a parametric bootstrap.

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The local normal and shear strain distributions were quantified using digital volume correlation, identifying dilatant shear bands.

A novel catchment characterisation system was developed, in which broad-scale landscape characteristics were quantified using existing datasets, types of sediment supply feature were identified in a field survey and their distribution across the catchment was quantified using a survey of air photographs.

The spatial distribution of vegetation canopy cover was quantified using photogrammetric modeling and landscape pattern metrics.

The discrepancy between observed test statistics and simulated predictive distributions in the various models was quantified using Bayesian p-values [ 48] and the L-criterion proposed by Laud and Ibrahim [ 53], both computed with MAPPS.

Prior information about test sensitivities and specificities and prevalence of infection was quantified using beta distributions.

The significance of enrichment for motif containing genes within each FunGroup was quantified using the hypergeometric distribution (see methods).

EMG was quantified using the amplitude probability distribution function (muscle loading) and gaps analyses (muscle rest).

The BV/TV was quantified by assessing the percentage of bone voxels within each VOI and the structural anisotropy was quantified using the star volume distribution method.

The distribution of doxorubicin in relation to tumor blood vessels was quantified using immunofluorescence.

Distribution of SSEA1 and SSEA4 expression in various cell populations was quantified using flow cytometry (Fig. 3A).

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