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All analyses were checked, and the correct datasets were used in the meta-analyses.
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Discovering the correct dataset in an efficient fashion is critical for effective simulations in the atmospheric sciences.
Open Context uses Git and Mantis Bug Tracker to track and correct dataset errors.
The novelty of prediction methods is that we optimized parameter settings for the prediction tool DBClus using an original correct dataset.
Both non-attenuation corrected and attenuation corrected datasets were reconstructed.
It thus appears that both corrected datasets have different and maybe contradictory information contents.
All images were iteratively reconstructed using post-emission transmission attenuation-corrected datasets (size 168; zoom 1; full width at half maximum (FHWM) 5.0 mm; iterations 4; subsets 8).
We baseline normalized the signal using the matched-pair normalization tool in PGS, by subtracting log2 IN signal intensity at each of 4.2 million from cell type-matched IP signals resulting in 6 corrected datasets (IP1 cor. and IP2 cor. for each cell line).
The covariate adjusted main model was then fitted using the 20 corrected datasets.
For a fair comparison, we also obtained these corrected datasets for using in GAGE.
Figure 8 contains LOD curves for 10-week insulin level with the original and corrected datasets.
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