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. …”

Largest changes in influenza vaccine rates, Pre- vs. Post-COVID-19. by Tyler B. Nofzinger (21560244)

Subjects:

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

Global Land Use Change Impacts on Soil Nitrogen Availability and Environmental Losses by Jing Wang (6206297)

“…However, how global land use changes impact soil N supply and potential N loss remains elusive. By compiling a global data set of 1,782 paired observations from 185 publications, we show that land use conversion from natural to managed ecosystems significantly reduced NNM by 7.5% (−11.5, −2.8%) and increased NN by 150% (86, 194%), indicating decreasing N availability while increasing potential N loss through denitrification and nitrate leaching. …”

The top 10 putative metabolites with the largest negative fold change between normal and thin cows. by Bhuripit Saraphol (20855573)

The top 10 putative metabolites with the largest positive fold change between normal and thin cows. by Bhuripit Saraphol (20855573)

A novel RNN architecture to improve the precision of ship trajectory predictions by Martha Dais Ferreira (18704596)

“…To solve these challenges, Recurrent Neural Network (RNN) models have been applied to STP to allow scalability for large data sets and to capture larger regions or anomalous vessels behavior. …”

Selection frequencies plotted in decreasing order. by Hannah P. Rowe (7830599)

AI KRegression by CHIN-CHENG CHU (20718575)

Presentation 1_Tracking priming-induced language recovery in aphasia with pre-trained language models.zip by Yan Cong (1491478)

Data Sheet 1_Tracking priming-induced language recovery in aphasia with pre-trained language models.zip by Yan Cong (1491478)

Average change in trust in science by country (n = 10,000). by Alain Abi-Rizk (8549358)

Subjects:

Trust change by gender. by Alain Abi-Rizk (8549358)

Subjects:

Trust change by age group. by Alain Abi-Rizk (8549358)

Subjects:

Multiple linear regression analysis of trust change predictors. by Alain Abi-Rizk (8549358)

Subjects:

Distribution of individual change in trust in science before and after the pandemic (n = 10,000). by Alain Abi-Rizk (8549358)

Subjects:

Trust change by education level. by Alain Abi-Rizk (8549358)

Subjects:

Trust change by source of science information. by Alain Abi-Rizk (8549358)

Subjects:

Post-pandemic trust in science survey. by Alain Abi-Rizk (8549358)

Subjects:

Trust levels before and after the COVID-19 pandemic (n = 10,000). by Alain Abi-Rizk (8549358)

Subjects: