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For example, measures of social approach and avoidance behaviour, generalization of anxiety, measures of mother child relationships, sensitivity of the autonomous nervous system to a standardized stressor, or the cortisol/corticosterone response to a standardized stressor is possible in various animal species and may be very useful from a translational neuroscience perspective.
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The AUC describes the relationships between sensitivity and specificity, a higher AUC implies a less steep trade-off between sensitivity and specificity.
Above we presented the numerical relationships between sensitivity, specificity and PAR% for binary and continuous biomarkers (Tables 1 and 2).
It consists of 32 questions focused on understanding of the given relationships, linguistic sensitivity, and vocabulary skills.
The themes highlighted the multifaceted nature of the AMHLO role from service entry to discharge, the establishment of meaningful relationships, cultural sensitivity, and community engagement.
The ROC curve is an indicator of the predictive performance of a developed test and depicts the range of relationships between sensitivity and specificity.
Table 2 shows the numerical relationships among sensitivity and specificity and PAR% of the quantification for various thresholds c in Figure 2.
This sensor exhibited a linear relationship between sensitivity and H2 concentration on a logarithmic scale.
A significant relationship between sensitivity to noise and sleep quality was also found.
To study the relationship between sensitivity and sensor dimensions, a simple model is presented in Figure 2.
The area under the ROC curve (AUC) reflects the relationship between sensitivity and specificity for a given test.
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