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The phrase "all categories of error" is correct and usable in written English.
It can be used when discussing different types or classifications of mistakes or inaccuracies in a particular context, such as in research, data analysis, or quality control.
Example: "The report outlines all categories of error that were identified during the experiment, ensuring a comprehensive understanding of the results."
Alternatives: "all types of error" or "every kind of error".
Exact(1)
Table 3 gives the corresponding data for all categories of error.
Similar(59)
Basically 5 categories of error are recognized.
Reason 8 distinguishes between three broad categories of error that have different cognitive causes: slips and lapses, mistakes, and violations.
Agreement was substantial for four of the 18 categories of error examined: technical error, failure in communication, systems failure, and no error (Table 8).
To maximize the likelihood of producing valid data in relation to a range of possible interpretations and applications of a tool, there are development processes that seek to protect the instrument against two categories of error; measuring less than the proposed construct (construct underrepresentation) or measuring more (construct irrelevant variance) [ 29].
9 There is, however, a consensus in these taxonomies and in the literature that show three recurrent categories of errors and vulnerabilities, relatively specific to primary care, and all related to time control: First, missed and delayed diagnoses 10 are considered to be the main cause of claims and allegations in primary care, especially for cancer and cardiac diseases.
The cases fell into categories of errors similar to those that plague doctors today, the authors say, classifying 11 of the cases as errors of judgment in which Cushing made the wrong choice during a surgery.
Two studies also reported changes in categories of errors.
Clear definitions of MAEs and the categories of errors included within definitions are required.
> The false positives included two categories of errors in the pipeline.
This study calls for more research into the prevalence of categories of errors, and interventional studies to reduce medical errors.
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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