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The bivariate analysis identified a model able to predict fluid responsiveness in 91 % of patients (AUC 0.92; Y = 24.9 + PPV*1.243 + Pdic*0.911 + CCEnor*0.004).
Taking into consideration the hydrochemical characteristics of this pit lake and the spatial distribution of the layers identified, a model that explains its seasonal limnological evolution is presented.
After all D F items were identified, a model was fitted in which − in addition to the latent variables − only D F items were regressed on the grouping variables.
The analysis identified a model with four distinct factors (Table 1).
We identified a model of evolution as a focal aspect of an introductory biology course, according to both participants.
After that, we identified a model of frequency distribution of the number of occurrences of FLs in a given TU.
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The standard approach for observers design is to identify a model and then define an observer/Kalman filter based on the identified model.
In the current control design approaches, measured data are used to first identify a model of the plant, then a controller is designed based on the identified model.
Neural network with a specific restricted connectivity structure is used to identify a model of a real-life process.
We present an algorithm, based on Pareto optimality, which mines model collections and identifies a model that offers a reliable prediction for a new chemical compound.
But if we identify a model with its description, then each new description yields a new model, which seems to be counterintuitive.
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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