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To mitigate potential bias, and to facilitate a comparison with GWAVA, we used the strictest data selection procedure outlined in Ritchie et al. (2014), i.e. selecting negative examples that fall within a 1000- nt window of some positive example.
PDF file providing details of (I) data selection procedure, (II) forecasting methods and (III) Diebold-Mariono test results.
The data selection procedure is summarized in Fig. 1.
Figure 1 displays the data selection procedure, giving 81 945 patients.
These human genes comprised group c. Figure 1 displays a diagram of the different approaches and the data selection procedure.
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However, we have not been able to completely remove these biases with simple data selection procedures.
But gradual development and changes in data selection procedures in the colliders raises an important epistemological concern.
A comparative evaluation of different quiet-time data selection procedures did not change the final results in this investigation, but did contribute to an improved correlation between model values and experimental observations.
The pseudo-data selection procedures (which included information from both the occurrence data set and the less-biased evidence consensus map) coupled with the model ensembling approach aimed to minimise this potential source of bias.
The data for this study are the routinely registered data of the selection procedure on the department of Utrecht from 2008 2010.
The stringent data selection and processing procedure applied in this study did reduce the scatter in the X time series at all observatories.
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data selection processing
data screening procedure
estimate selection procedure
data preparation procedure
data admission procedure
data selection scheme
data selection policy
data analysis procedure
data generation procedure
data transmission procedure
data augmentation procedure
data transformation procedure
data gathering procedure
data extension procedure
data mining procedure
data selection homogenization
data assimilation procedure
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