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To test these predictions we conducted two related studies.
To test these predictions we conducted a magnetoencephalography (MEG) experiment on human subjects.
To help generate a clear set of predictions, we conducted a norming survey asking 28 participants on Amazon's Mechanical Turk (www.mturk.com; [18]) to describe what should be done to solve a literal virus or beast problem.
As one test of these predictions, we conducted a behavioural masked priming study, assessing whether equivalent repetition priming would be obtained for within script and across script prime-target pairs.
To test these predictions we conducted both field observations and lab experiments.
In order to validate 22 selected ab initio predictions, we conducted RT-PCR using RNA from M. perniciosa saprotrophic mycelia.
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To test this prediction we conducted a phylogenetically controlled comparative study of phallus size and vaginal morphology in 16 waterfowl species.
To test this prediction, we conducted the following analyses.
To examine this prediction, we conducted an individual differences analysis on the participants in all four experiments.
To test this strong prediction, we conducted a multivariate pattern classification analysis using a leave-one-subject-out cross-validation scheme.
To calculate the best cut-off value for permeability in normal-appearing white matter for multiple sclerosis prediction we conducted a ROC analysis, yielding an area under the curve of 0.77 [95% confidence interval (CI) 0.60 0.93], P = 0.005 (Table 3).
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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