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However neither system in this study offered additional ranking interpretation of the nutritional quality of products, thereby limiting their full ability to inform consumers and to promote continued product improvements.
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The study also focuses on the impact of the methodology settings on the obtained chemical route rankings and their interpretation.
We address feature selection in terms of the gene ranking problem and the interpretation of the obtained spot-related lists using concepts of molecular function.
This study established a framework for the in vitro evaluation of cancer-relevant bioassays for comparisons of insulin analogues, and specifically consolidated earlier studies that determination of the cell-specific IGF-IR/IR ratio is crucial for the interpretation of ranking relative biological activities.
This study has built on that literature and established a cancer-relevant, dose response equivalent and time-dependent framework for evaluating the effect of insulin analogues in vitro and identified the importance of determining the cell-specific IGF-IR/IR ratio for the interpretation of ranking relative biological activities.
However, the width of the credible intervals around the posterior median ranks was considerable, and so we urge caution in the interpretation of rankings and the probability that treatments are "best".
Lemmers et al recently proposed a best-case and worst-case scenario ranking and illustrated this approach on the dataset we also use in this paper.[ 5] Marshall et al. calculated 95% confidence intervals to the ranks.[ 6] The aim of this study is to present another method: the Expected Rank (ER), which prevents over interpretation of the rankings.
This ambiguity hampers not only the interpretation of the ranking result but also the comparison with the rankings produced by the other methods.
In the EFA no reverse coding was used, however, to ease interpretation of the rankings we reverse coded the negatively worded items.
For ease of interpretation, we transformed friend-rank and perceived rank by multiplying by -1 so that high-ranking individuals, such as friend number 1, are denoted by numerically greater values than low-ranking individuals, such as friend number 10.
Accurate P-values without ranking stability question the robustness of biological interpretation.
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CEO of Professional Science Editing for Scientists @ prosciediting.com