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_ largest » _ large (Expand Search)
largest decrease » larger decrease (Expand Search), marked decrease (Expand Search)
values decrease » values increased (Expand Search)
teer decrease » mean decrease (Expand Search), greater decrease (Expand Search)
we decrease » _ decrease (Expand Search), a decrease (Expand Search), nn decrease (Expand Search)
_ largest » _ large (Expand Search)
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TITAN thresholds and percentile estimates for benthic macroinvertebrate and diatom communities deemed to be sensitive decreasers or tolerant increasers. The thresholds represent the largest fsum <i>z</i> value in the main data analysis run (i.e., the median), whereas the 5<sup>th</sup> and 95<sup>th</sup> percentile change points are determined from 500 bootstrap replicate runs....
Published 2025“…<p>TITAN thresholds and percentile estimates for benthic macroinvertebrate and diatom communities deemed to be sensitive decreasers or tolerant increasers. The thresholds represent the largest fsum <i>z</i> value in the main data analysis run (i.e., the median), whereas the 5<sup>th</sup> and 95<sup>th</sup> percentile change points are determined from 500 bootstrap replicate runs. …”
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Table 1_Multi-generational adaptation to Solanum nigrum increases reproduction and decreases microbial diversity of Aphis gossypii.docx
Published 2025“…The fifth generation of A. gossypii (T5) exhibited the strongest adaptability to S. nigrum, demonstrating notably higher values of r (intrinsic rate of increase), λ (finite rate of increase), and fecundity compared to the first generation of A. gossypii (T1). …”
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Forest plot of ROR values used to assess gender differences in penicillamine-related AEs.
Published 2025Subjects: -
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Paeameter ranges and optimal values.
Published 2025“…Additionally, considering the imbalanced in population spatial distribution, we used the K-means ++ clustering algorithm to cluster the optimal feature subset, and we used the bootstrap sampling method to extract the same amount of data from each cluster and fuse it with the training subset to build an improved random forest model. …”
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