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Submissions were scored by a metric based on the sum of the squared prediction errors (Figure 2B).
Submissions were scored based on the probability that a random solution to the challenge would achieve at least as many correct protein identifications as the submitted solution.
Submissions were scored using Spearman's rank correlation coefficient between the predicted and measured gene expression at each of the eight time points.
Submissions were scored by the probability that a random assignment table would result in as many correct identifications as achieved by the participant.
In this study, community submissions were scored an average of 81% for completeness, 97.2% for experimental support and 93% for appropriate level of term specificity when compared with annotations that would have been made by trained biocurators based on the same publications.
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Each submission was scored such that a question with rank 1 was given 10 points, rank 2 had 9 points and rank points went down such that rank 10 was given 1 point.
After predictions from participants are collected via website submissions, the results will be scored using metrics such as the Area Under the Precision versus Recall (AUPR) curve.
In all cases, the reviewers assessed the manuscripts at least twice and all submissions were ranked based on the reviewers' scores, in accord with earlier InCoB publications [ 3].
In general the precision scores of the team submissions were slightly better than the corresponding recall.
No viable submissions were received.
Almost 700 submissions were received.
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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