Sentence examples for the same level of specificity from inspiring English sources

The biomarker molecular signature is composed of IL-1a, TNF-a, IL-3, EGF and G-CSF and has the same level of specificity and sensitivity as the original 18-protein signature proposed by Ray et al. [2] in late 2007, who introduced this important dataset in the literature.

A higher sensitivity at the same level of specificity, results in a better performance.

The performance of the causal graph-based model is very similar and not statistically different: it achieves 81% sensitivity at the same level of specificity and 70% specificity at the same level of sensitivity.

In the scanner, subjects were presented only written sentences describing the age, location, and occupation/usage of the people, places, and hammers, ensuring that all categories were processed at the same level of specificity and with the same types of information (e.g., see Table 1).

This information is vital for accurate prediction of novel instances of these ELMs but it presents an unwelcome challenge for de novo SLiM prediction benchmarking, as it is impossible for computational tools to achieve the same level of specificity given the lack of information in the input data.

Our task allowed us to directly compare 3 familiar categories for which subjects had a great deal of previously acquired conceptual knowledge, while being reasonably certain that subjects processed the categories at the same level of specificity and with the same amount of knowledge about the specific exemplars presented in the scanner.

Note that both rules are problem-related, representing approximately the same level of semantic specificity.

In comparison, the performance of CEA alone would have reached a sensitivity of only 37% (95%CI: 29-44%) at the same level of specificity at 86%.

That is, our calibrated PSSM-FMs operate on the same level of sensitivity as hmmsearch employing the pHMM, but with possibly reduced specificity.

In particular, computer-based forms have the potential to achieve the same levels of sensitivity and specificity as their paper-and-pencil counterparts, but by using fewer items on average [ 18, 19].

The growth MRI provides the same degree of specificity for chief executives seeking to grow their companies.