Femur length anomalies tend to decrease with later phenology (greater day of year of adulthood anomaly) regardless of elevation or species’ seasonal timing. by César R. Nufio (11646271)

Overview of study procedures. by Matthew G. Vinson (22593374)

“…Intent to decrease OTC NSAID use increased more from baseline to immediately post-intervention in VIDEO vs. …”

COVID-19 epidemic curve and the timing of the restrictions for the Greater Toronto Area between February 23, 2020 and December 13, 2020. by Siyi Wang (1412581)

Change in physiologic data over time. by Katharyn L. Flickinger (4759323)

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. …”

Data Extraction Sheet: A sheet that contains the data that we extracted from the included studies. by Mohamed R. Abdelraouf (21501468)

Relationship between axial strain and time curve. by Dengke Yang (842532)

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

Screening Sheet: A sheet that contains the full screening process that we used to include or exclude any study. by Mohamed R. Abdelraouf (21501468)

Overview of the WeARTolerance program. by Ana Beato (20489933)

“…This research evaluates the "WeARTolerance’’ arts-based program in reducing mental health stigma among diverse youths. …”

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>…”

Differences in mean number of papers (top) and co-authors (bottom) depending on (1) NI membership and (2) time joined NI. by William C. Barley (8915282)

Flow diagram showing number of subjects included in the study population. by Jung-Tae Kim (8997767)

Subjects:

Negative ion mode significant differential metabolites (Fold Change greater than 2 or less than 0.5). by Peng-fei Han (694841)

Positive ion mode significant differential metabolites (Fold Change greater than 2 or less than 0.5). by Peng-fei Han (694841)

Time to onset of major depressive disorder by intervention group. by Si-Jing Chen (15350263)

Hemodynamic and respiratory changes over time. by Katharyn L. Flickinger (4759323)

Time series plots: Alcohol consumption. by Luis Alberiko Gil-Alana (14659817)

“…The results indicate that only France displays a significant negative trend and thus a continuous decrease in the level of alcohol consumption. For the rest of the countries, the time trend is insignificant. …”

Schematic representation of the experimental protocol over time. by Vanessa Wellauer (18408477)

Time between symptom onset and diagnosis. by Nicole Michelén Ströfer (19269154)