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In CoryneRegNet, the data are first imported into a data repository, thereby creating a dataset concept for each biological entity, for instance genes, proteins or transcription factors, and a dataset relation for any connection between two concepts.
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For simplicity we here consider only the much larger PACES dataset in relation to ethnic bias.
UCAS applicants therefore have somewhat higher grades than the population as a whole, which would be expected as only the better A-level candidates will apply to UCAS, but otherwise have a broadly similar A level distribution to that found in YCS.. Figure 8 shows the distribution of A level grades in the UCAS dataset in relation to ethnicity.
Finally, we analyzed the ChIP-chip dataset in relation to previous genome-wide studies in hESCs (Abeyta et al., 2004; Boyer et al., 2005; Guenther et al., 2007) for features that might distinguish class I and class II genes and found two statistically significant differences.
Some of the sentences of the BC-PPI dataset contained relations between proteins which had not been annotated in the corpus for not being a protein-protein interaction in the strict sense.
Interestingly, in all datasets this relation followed an exponential function.
Nonetheless, a number of studies have found plausible biologic associations with cartilage loss on MRI in this dataset, including relations to alignment [ 40], bone marrow lesions [ 41], and meniscal abnormalities [ 42].
In both datasets, in relation to aggregate endorsement frequencies, for all items, three of five response categories met the >10% criterion, but two of five response categories were <10% (between response categories 4 and 5) and 10 of 12 items fell outside the skewness criterion (−1, +1).
The approach adopted involves expert opinion of how the two land cover datasets relate under a scenario of idealised relations.
The gold dataset contains 102 relation annotations while our annotator produces 397 relation annotations.
Here, the sequence of TESTS paired consecutively as CXR and LP, LP and UA, and UA and abdominal CT are unannotated in the dataset with a relation, but the identification classifier classifies them as having a relation.
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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