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The Standard ensures reproducibility of the data, and provides visibility/reasoning for any parameters set in the calculation, such as accuracy thresholds, calculation pathways, and mesh dimensions.
Now, in two papers published today in Science, the group reveals in-depth analyses of the data and provides an unparalleled glimpse at human evolution.
It now uses an approach that created good time intervals (GTIs) to filter the data and provides some guidance on how to determine the target period.
Data from published screens are available to the public through a highly configurable interface that allows detailed examination of the data and provides access to a number of other databases and bioinformatics tools.
The algorithm uses a scale-by-scale model building strategy that searches for B-splines at each scale fitting adequately to the data and provides smoother approximations than the original Multivariate Adaptive Regression Splines (MARS).
The third section describes the data and provides descriptive statistics.
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Cloud computing allows a third-party service provider to manage the data and provide services directly to the end-user.
contributed to the interpretation and analysis of the data and provided scientific knowledge.
J.M.B. provided the hAID model, analyzed the data and provided conceptual advice.
All authors contributed to the interpretation of the data and provided input to the final manuscript.
All authors interpreted the data and provided comments on the paper.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.
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CEO of Professional Science Editing for Scientists @ prosciediting.com