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The described LiDAR metrics were generated from all returns.
For E. coli these metrics were generated using the CodonW software package [ 37].
Control metrics were generated and passed for each array (Robust Multichip Analysis performed with Affymetrix Expression Console Software 1.1; Affymetrix).
Capture and read length metrics were generated and exemplified by the NA12878 SMS/PTLS 6 Kb insert PacBio capture library in Figure 2.
For all three datasets, confidence metrics were generated using only statistical and topological predictors, such as the number of interaction partners and a local clustering coefficient.
In addition, quality assessment metrics were generated for each scanned image and were evaluated based on empiric data from previous hybridizations and on the signal intensity of internal standards that were present in the hybridization cocktail.
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To create the artificial population, a large multivariate dataset containing NFI field observations and ALS metrics was generated using a copula function fitted to the empirical observations, and then it was generalized over the study area using satellite imagery and nearest neighbor imputations.
The truncation errors contained in the inverse metrics are generated by the spatial schemes.
An array of metrics for segmented FVC analyses, including a variety of area metrics, patch metrics, shape metrics and diversity metrics, was generated.
In so doing, a multi-temporal data cube (via a series of annual proxy composites) and a set of change metrics are generated.
A set of LiDAR metrics was generated for each of the 113 sample plots using Fusion's CloudMetrics utility.
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