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Experiment 3, a smaller experiment in which we manipulated the stimulus size (see below), used classes L, M and N (class distributions not shown; see Fig. 9 for two exemplars).
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We examined how these metrics can improve our understanding of population-level responses to forest disturbance, using datasets for two exemplar species of terrestrial salamanders resident to the Pacific Northwestern USA.
Simulations were shown for two exemplar cases (side step or back step).
This finding is illustrated for two exemplar participants in Figure 2.
Normalized quantitation values for three exemplar proteins were plotted on 3D axes.
Figure 5 displays these within-participant discrete functions for three exemplar measurement systems.
Additional file 3 summarizes the results of the above calculations for four exemplar probesets in all three rounds.
The VPG is compared to the PG with respect to the ACS across the fluctuating edge probability, p, for four exemplar disordered-lattices shown in Figure 8, and for the four proteins shown in Figure 9.
Calcium response (ΔF/F) traces for six exemplar neurons from a single mouse, for sets of three trials before (panel on the left), and after (panel on the right) task learning.
A supplementary analysis was also carried out to compare performance accuracy for the two exemplars of neutral faces (neutral1 vs. neutral2); this analysis showed no significant results, t(19) = 0.66, p >.5, so the data from these two exemplars were collapsed into a single neutral face category.
For example, presenting two exemplars from confusable categories simultaneously can support memory for those exemplars and classification of later novel category members because it enables learners to discriminate between categories (Wahlheim, Dunlosky, & Jacoby, 2011).
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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.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com