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. …”

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

Univariable and multivariable analysis of patients who returned to the same surgeon or a different for a subsequent hand surgery after a carpal tunnel release. by Scott J. Halperin (17835402)

Additional file 6 of Decreased complement 4 and interleukin-10 as biomarkers in aqueous humour for non-exudative age-related macular degeneration: a case control study by Juliane Schikora (20871169)

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)

Interaction plot with 95% confidence intervals generated from the GAM regression model 1 in Table 2 examining initial ED SBP and management group interactions. by Randeep S. Jawa (20489181)

GPT-4 results in decreased error rate for all tasks with increasing complexity when compared to GPT-3.5-turbo. by Jacqueline A. Jansen (14894276)

Analysis of errors of the AI model on accuracy and decision times for different tasks during the retrospective reader study. (a) by Kerol Djoumessi (21349992)

Sex-independent volume changes in ECM. by Alicia Comino Garcia Muñoz (22075399)

“…<p>(A) T₂-weighted sagittal images of the brain of the same male mouse acquired before PbA inoculation and at day 5 p.i. …”

Sex-specific lifespan and gene expression. by Frederic Zimmer (7312322)

“…The experiment was started by culturing the same number of adult stage males and females (indicated by an asterisk), as before the sexes cannot be visually distinguished. …”

Trend of all service utilization for all conditions between 2016 and 2022. by Fernanda Talarico (807333)

CONSORT diagram. by Aurélia Lépine (637511)

“…Young women are twice as likely to be living with HIV as men of the same age and account for 64% of new HIV infections among young people. …”

Reasons for consultation. by Aurélia Lépine (637511)

“…Young women are twice as likely to be living with HIV as men of the same age and account for 64% of new HIV infections among young people. …”

Result of rapid test vs. laboratory ELISA tests. by Aurélia Lépine (637511)

“…Young women are twice as likely to be living with HIV as men of the same age and account for 64% of new HIV infections among young people. …”

Response rates and attrition by arm. by Aurélia Lépine (637511)

“…Young women are twice as likely to be living with HIV as men of the same age and account for 64% of new HIV infections among young people. …”

Data set. by Aurélia Lépine (637511)

“…Young women are twice as likely to be living with HIV as men of the same age and account for 64% of new HIV infections among young people. …”

Project timeline. by Aurélia Lépine (637511)

“…Young women are twice as likely to be living with HIV as men of the same age and account for 64% of new HIV infections among young people. …”

Summary characteristics at baseline. by Aurélia Lépine (637511)

“…Young women are twice as likely to be living with HIV as men of the same age and account for 64% of new HIV infections among young people. …”

Feature engineering. by Youli Jiang (15249070)