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The models determined for this paper only estimate arsenic concentrations for recent aquifer conditions and may not reflect past conditions when pumping was lower and water levels were higher.
Phylogenetic analyses were performed using maximum likelihood (ML) and Bayesian methods, with optimum substitution models determined for each alignment based on the Akaike Information Criterion using ProtTest 2.4 [ 51].
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The model is validated and constants of the model determined for simple test cases.
The best evolutionary model determined for the sequences was TrN + I + G.
We applied the second step of our model selection method to these profiles to select models common to all five time-of-day profiles, using as a subset of parameters the ones in the model determined for our irrigated field data instead of the hdi pre-selection.
The reaction rates used for the models determined by fitting phosphotransfer in vitro experiments [ 16, 31].
The common reactions in all 4 models were determined for each functional category and the unique reactions in only one model but not in the other models were also determined (Table 2).
Regression parameters used in two MR prediction models, namely the Bulk Stress Model and 2-Parameter Model, were determined for the CG geopolymers.
To preserve the sufficient events per variable, from the significant univariable parameters, all possible two-variable models were determined for imported A. baumannii carriers (n = 16) and all possible three-variable models were determined for acquired carriers (n = 32).
Adsorption parameters for the Langmuir and the Freundlich isotherm models were determined for all organic substances tested.
Amino acid likelihood substitution models were determined for each gene matrix with ProtTest3 (Darriba et al. 2011).
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