Sentence examples similar to redundant validation from inspiring English sources

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However, the markers that are redundant for our validation panel, could be critical for discrimination when applying the MOL-PCR assay to future collections of S. Typhimurium and S. 1,4,[5],12:i:- isolates.

Multiple studies in a variety of species, including alfalfa [ 14, 24, 28, 102– 105], have illustrated the consistent correlation between gene expression measured by RNA-seq and by qRT-PCR, rendering this validation redundant.

This operation collects the data from each channel and merges it after data validation using redundant information coming along with the data.

However, the CORE-OM in Swedish, English, Italian and Japanese has been cross-validated with other measures like the BDI, BAI, GHQ and SCL [ 7, 8, 12, 13], and another cross-validation seems redundant.

This detailed information page for an adjusted motif in each dataset contains the following content: i) The basic information about the motif including cell and tissue type the motif occurs, datasets the motif occurs, the motif consensus, the motif PWM, the motif logo and the corresponding non-redundant motif; ii) The validation information with known motifs in seven motif databases.

A systematic method to design optimal redundant sensor networks applying data validation theory is described.

Consistencies of expression levels were confirmed by validation across multiple redundant probe sets.

As shown in Table  I, item-generation involved four stages: generating potential items; eliminating redundant, irrelevant and outlier items; validation among people with fertility problems, and cross-cultural survey of acceptability and feasibility.

With an appropriate (lambda) selected using a cross-validation scheme, all redundant features are removed from the model by forcing their coefficients to be zero.

While older methods could only be tested on a case-by-case basis or on a small set of similar complexes, large-scale statistical analysis and validation on non-redundant benchmarks has become the norm.

The selection of number of nodes for an ANN remains an important issue as an overparameterized ANN gets trained along with the redundant information that results in poor validation.

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