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Using our measurements of salinity on the 25th December to validate all these scenarios, we arrived at the most probable estimates of the variables which could have facilitated a drop in the salinity to 12.26 psu.
It must, however, be emphasised that these most probable estimates of the dates when the OW-NW begomovirus split occurred (i.e. 29.6 and 20.3 MYA) were derived considering only the most probable integration dates of the two GRD elements (i.e. the median estimates of these integration times).
We considered these the most probable estimates for each commodity (Technical Appendix 2).
To provide a range for the most probable estimates, we determined a minimum estimate by attributing illnesses to commodities implicated only in outbreaks where illness was transmitted by simple foods and a maximum estimate by including complex food outbreaks and attributing the outbreak illnesses to each ingredient in the implicated food (Technical Appendix 1 Table 3).
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Iterations are terminated at the solution which yields the most probable estimate of the emission densities while matching the sinogram data.
The most probable estimate is the set of ϕ and α that minimizes the evaluation function E, as defined by Equation 7, i.e., the set that maximizes p ϕ,α|V P,V S ).
The numbers provided in the Results section are the most probable estimate, unless stated otherwise.
Numbers of hospitalizations are the most probable estimate, as described in Methods.
Numbers of illnesses are the most probable estimate, as described in Methods.
Numbers of deaths are the most probable estimate, as described in Methods.
NS Non significant or * significant at P ≤ 0.05 a Most probable estimate of population growth rate calculated by Bayesian analyses using the program Lamarc 2.0 [29, 29].
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