The ROC curves and AUC values of the diagnostic model. by Zhe Wu (582498)

Boxplot comparing Ct values for HD in flies and clothes. by Philippe Ndzomo (17706039)

L* Value Increases with Increasing Zinc Oxide Percentage. by Alexandra M. Maldonado López (22127340)

The spike-in of synthetic hsa-lest-7a-5p miRNA decreases the Ct Values of extracted small RNA samples. by Marc Van Der Hofstadt (1423027)

CT Values of reference materials. by Guosong Jing (20840261)

ROC curve and AUC value of all models. by Tiago de Oliveira Barreto (20485207)

“…As for Specificity (82.94%) and ROC-AUC (82.13%), the Multilayer Perceptron with SGD optimizer obtained the highest scores. …”

Data Sheet 1_Correlation analysis of osteoporosis and vertebral endplate defects using CT and MRI imaging: a retrospective cross-sectional study.pdf by Song Hao (5700608)

“…</p>Conclusion<p>There was a correlation between OP and the size of the vertebral endplate defect, and the defect size increased with decreasing bone mass. According to our results, vertebral endplate defects are more likely to occur in elderly individuals, females, and individuals with OP. …”

Change in computation time for an increase in number of nodes <i>N</i> and number of people in system <i>K</i> (<i>C</i> = 3). by Shinya Mizuno (3689788)

Analysis of stress-related gene expression in cherry shrimp (<i>N</i>. <i>davidi</i> var. red). by Wei-Wei Hou (3405947)

Gaussian model fitted of the number of dogs detections of SARS-CoV-2, depending on the cycle threshold (Ct) values of RT-qPCR tests for SARS-CoV-2. by Víctor M. Vidal-Martínez (18707335)

Subjects:

Cycle threshold values at which a specific number of dogs out of 11 dogs was able to detect SARS-CoV-2 in samples from Merida, Yucatán, México. by Víctor M. Vidal-Martínez (18707335)

Subjects:

Results of a dog’s detections after exposure to sweat samples from positive and negative people to SARS-CoV-2, together with the Ct values of the RT-qPCR test of each person partic... by Víctor M. Vidal-Martínez (18707335)

Subjects:

Sensitivity and specificity of 11 dogs trained to detect SARS -CoV-2 from the sweat of positive and negative people from Mérida, Yucatán compared with the reference test (RT-qPCR).... by Víctor M. Vidal-Martínez (18707335)

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Details of the 11 fully trained dogs exposed to sweat samples of SARS-CoV-2 positive and negative humans. by Víctor M. Vidal-Martínez (18707335)

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Area under the curve (AUC) for external validation performance. by Junichi Kushioka (12236447)

AUC statistics as calculated from simulated time series. Each statistical metric was calculated within sliding windows, throughout the pre-critical interval. We considered five-, fifteen-, and thirty-day sliding windows. Given that the temperature of the system increased to 12°C on day sixty, we also considered three pre-critical intervals: Days 1 to 60, Days 20 to 60, and Days 30 to 60. To evaluate trends in these metrics, we calculated Kendall’s rank correlation coefficient during the pre-critical interval, and compared control (constant temperature, non-epidemic) and warming (warming treatment, epidemic emergence) coefficients across simulations and experimental populations by calculating the area under the curve (AUC) statistic. Values less than 0.5 suggest that a decrease in the statistical metric indicates emergence, while values greater than 0.5 suggest that an increase in the statistical metric indicates emergence, with more extreme values indicating stronger tre by Madeline Jarvis-Cross (22394247)

“…To evaluate trends in these metrics, we calculated Kendall’s rank correlation coefficient during the pre-critical interval, and compared control (constant temperature, non-epidemic) and warming (warming treatment, epidemic emergence) coefficients across simulations and experimental populations by calculating the area under the curve (AUC) statistic. Values less than 0.5 suggest that a decrease in the statistical metric indicates emergence, while values greater than 0.5 suggest that an increase in the statistical metric indicates emergence, with more extreme values indicating stronger tre</p>…”

TITAN increaser diatom heatmap. by Brent J. Bellinger (21156150)

<i>M</i>. <i>separata</i> herbivory primes systemic leaves for increased JA and JA-Ile. by Bo Fan (383210)

Individual values for figures. by Robert S. Leigh (10329847)

Moran’s I value, Z value and P value of CCD-GFEE. by Dalai Ma (17847101)