Your English writing platform
Discover LudwigExact(2)
The analysis of variance results showed the significant models could precisely predict the percentage removals of phenol and 4-CP, indicating models reliability.
Hydrogen and carbon monoxide levels within the flame brush are raised by stratification, indicating models with laminar premixed flame chemistry may not be suitable for stratified flames.
Similar(57)
Observed versus predicted response in genetic variation (AFLP markers) between sampling localities, indicating model performance.
Observed versus predicted response in morphological variation between sampling localities, indicating model performance.
Well-fitting models show non-significance on this test, indicating model prediction is not significantly different from observed values.
Model fit errors were small (< 0.25%) for Group A, Group B and the entire cohort (A + B), indicating model fitness.
eBoldface names and architectures indicate models in which ensemble classifications were determined using the averaging method.
These findings indicated models high validity in predicting the AB1 removal by both of biomasses.
Apart from general frameworks for foresight evaluation, there can be indicated models devoted strictly to the foresight impact evaluation.
* indicates models were fitted with unstructured variance-covariance otherwise compound symmetry models were fitted.
The akaike information criterion indicated models with interactions were better fitted.
Write better and faster with AI suggestions while staying true to your unique style.
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