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

TITAN decreaser macroinvertebrate heatmap Heatmap of sensitive (i.e., <i>z-</i>) macroinvertebrate taxa (y-axis) to at least one of the five stressors, in decreasing order of numbe... by Brent J. Bellinger (21156150)

Data Sheet 1_Emotional prompting amplifies disinformation generation in AI large language models.docx by Rasita Vinay (21006911)

“…Introduction<p>The emergence of artificial intelligence (AI) large language models (LLMs), which can produce text that closely resembles human-written content, presents both opportunities and risks. …”

Explanation of condition nodes and decision nodes in the SCM, ordered by decreasing centrality. by Stella D. Juventia (19961247)

Mean values of physical parameters of rock samples. by Dengke Yang (842532)

Feasibility of AI-powered assessment scoring: Can large language models replace human raters? by Michael Jaworski III (22156096)

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)

“…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>…”

Kolmogorov-Smirnov (KS) test for the different parameter value pairs at a 95% confidence level. We tested the null hypothesis for all parameters: The RMSEs obtained for one pair of... by Cyrine Chenaoui (22177098)

Calculation of peak force and impulse values from trial with overlap. by Leena Inkilä (20614460)

Decrease in loss during the training process. by Muhammad Idrees (92773)

Calculation of peak force and impulse values from force plate data. by Leena Inkilä (20614460)

Data values for figures. by Fermin E. Guerra (6084545)

Input parameter ranking for discrete measurements: Each column displays parameters (P) and their influence values (E) calculated using Eq 11, shown in decreasing order of influence. Results are presented for progressively expanding discrete measurement sets (from Set 1 to Set 3F). Only parameters with influence values greater than 0.01 are shown. by Harry Saxton (19165441)

“…Only parameters with influence values greater than 0.01 are shown.</p>…”

TITAN increaser macroinvertebrate heatmap Heatmap of tolerant (i.e., <i>z</i>+) macroinvertebrate taxa (y-axis) to at least one of the five stressors, in decreasing order of number... by Brent J. Bellinger (21156150)

Changes in blood pressure, HbA1c, blood lipid and liver function-related indicator values compared with baseline values in all patients over time. by Jia Song (495396)

Results obtained from different regression models along with their respective AIC values. by Farzana Afroz (20700794)

Subjects:

Changes in inflammatory cytokine levels compared with baseline values in all patients over time. by Jia Song (495396)

S2 File - Factors influencing effective decrease of controlled attenuation parameters in metabolic-associated steatotic liver disease: A multilevel linear regression analysis at Va... by Sonsawan Sangprasert (22772538)

Changes in the UACR and urinary β2-MG levels compared with baseline values over time. by Jia Song (495396)

Changes in the eGFRs and serum potassium levels compared with baseline values in all patients over time. by Jia Song (495396)