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However, the differences between the different label formats were only moderate.
The pair-wise comparison task showed that, overall there were only modest differences between the different label formats.
We also found differences in the efficacy of the different label formats to support the correct decision about healthier food variants.
All other comparisons yielded significant differences in the number of correct choices between the different label conditions (p < 0.01).
Notice that the proposed algorithm KAOGINCSSL and the DWM-NB algorithm have performed similarly throughout all the different label percentages domains, with exception to the experiment with 10%% of labeled patterns where the KAOGINCSSL algorithm presented a better performance.
The "discriminatory" aspect of the key new (sequence-dependent) contribution is most evident in forms like that above, where we have a likelihood ratio for the observed sequences given the different label "classifications" chosen.
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Cell viability was >90% for all cell labeling protocols with no noteworthy differences found among the different labeling methods and incubation times.
Thus, we can not exclude that a wider selection of foods might yield a better chance for the different labels format to produce differences in food choice.
They also agree that there are differences to be marked between them, hence the different labels for them.
This result indicated there were differences in the cDNA population produced by the different labeling methods, which caused different hybridization characteristics.
So would the different labels impact the likelihood of purchase for men and women differently?
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com