The phrase "a set of corrected" is correct and usable in written English.
It can be used when referring to a collection of items that have been revised or amended in some way.
Example: "After reviewing the feedback, I compiled a set of corrected documents for the final submission."
Alternatives: "a collection of revised" or "a group of amended".
But there was a bombshell in his letter, the announcement of a fait accompli: "I send you herewith a set of corrected galleys of Camus's L'Étranger, which we have decided to call The Outsider, both because we consider this a more striking and appropriate title than The Stranger, and because Hutchinson's recently called one of their Russian novels The Stranger".
After demonstrating the impact of the reservations and payment bugs, we then presented a set of "corrected" results for the brokerage model, intended to replace those presented by R&C.
The effects of the reservations bug (Section 'Experiment 2: the reservations bug') and payment bug (Section 'Experiment 3: the payment bug') identified in R&C's implementation are then demonstrated, before a set of "corrected" results for R&C's model are presented (Section 'Experiment 4: corrected replication of R&C's brokerage model').
It considers for each erroneous read a set of correcting reads such that all reads share a (k − 1 ) -mer left of the error and the set of correcting reads share a k-mer that ends with the correct base, which outvotes the erroneous base.
The outcome is a set of bias corrected variables that are not assessed for bias in their joint dependence structure, nor biases in all attributes at other time scales (such as daily and monthly and annual) except the one under consideration.
To isolate differences in obtained mean values of depth, dive frequency and variance in Ta and Tb between regions and during transit, we used a multi-comparison Analysis of Variance with a set of Bonferroni corrected t-tests [48] and reported when significant.
The set C is a set of error correcting codewords c of length n and x represents a bitstream of length n, termed witness (biometric data).
Setting of correct priority of the view makes it distinct from the others.
It may work in a world where there is a finite set of "correct" answers, but that is rarely true in the world of humanist learning.
If a high cut-off qvalue is selected, then a large set of correct term pairs are included, but there will also be a large number of correct term pairs that are excluded.
