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To define the most optimal combination rules, we compared the average performances for the fixed, trained and advanced combination rules in Figures 4b to 4d, respectively.
When the number of deaths could be determined for both the ClinicalTrials.gov record and the corresponding publication following the rules, we compared the numbers between the record and the publication.
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In order to assess the performance of the proposed FCS scheduling rule, we compare it the with the state-of-the-art strategies shown in Table 1.
With a small sample size it is not possible here to derive clinical prediction rules [33] [38], however we compared three alternative case definitions and found that the most predictive (with highest area under the ROC curve) was at least two of the following signs and symptoms: fever ≥37.8°C, cough, headache, sore throat, aches or pains in muscles or joints (Appendix Table S1).
Question (2)—representing the main claim that we intend to verify is sufficiently straightforward: keeping other variables unaltered (namely, using always the same linearisation rules), we will compare different versions of our system using various language models (FLM and word n-gram alike).
In order to test for acquired dependence upon citrate (i.e., rule out H0), we compared growth rate and yield on glucose either with or without citrate for the ancestors and one clonal isolate from each of the 12 populations of the LTEE at 50,000 generations.
To rule out this hypothesis we compared behavior using only the first round of the game.
To rule out this bias, we compared the growth rate of small colonies under two conditions: in isolation and when paired with a large colony.
To rule out this objection, we compared scrambled and control stimuli.
We compared the rules generated with those added to the guidelines in a newer version, to examine their similarity.
In order to rule out any systematic bias, we compared the follow-up groups that did or did not complete brain imaging on a number of demographic and cognitive variables and could not detect any significant differences.
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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