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The underlying question is more subtle: Is saying "I misspoke" a fair way of accounting for a meaningless error or is it a refusal to own up to a more serious mistake?
A meaningless error code is presented to the user, as if he'll know what to do with that.
The list of suggested problems includes a variety of other meaningless error codes, but not the one that this user received.
The first reason is that seismic imaging algorithms usually involve numerous iterations, which can lead to overestimation of the error bounds and derive a meaningless error function.
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However, this characterization is meaningless if the errors of the data σ f i i = 1 N are either (i) quite larger than their deviations from the model values, i.e., if σ fi > > |f i - V(x i ; α)|, or (ii) quite smaller, i.e., if σ fi < < |f i - V(x i ; α)| (e.g., see Figure 3).
However, as represented in Fig. 9, the FC scheme with a low threshold value is meaningless due to the error performance loss.
However, these errors become meaningless after the calibration procedure introduced in Section 5.3, which corrects the power distribution so that it resembles the real propagation case according to the recorded measurements.
These sorts of continuity errors are meaningless to a child (unless that child is me, and he is a huge dork that has a room full of James Bond books) but if you have to do that much character gymnastics, it stands to reason that your project is wrongheaded.
Zooming into annotations with several evidences brought the numbers closer, i.e. 'increased' the performance, but this was achieved at raising the standard errors to meaningless values (Supplementary Table S8).
Since PCA involves a normalization step, standard deviations of the PCs can be used as an index of variability (using the coefficient of variation is meaningless in this case): the error bars representing the standard deviations of the PCs in Figure 9B already suggest that variability in phenotype is higher for immature classes (1 and 2) than for the mature class (3).
Robot designers needed numerical methods or trial-and-error solvers using meaningless equations.
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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