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. …”

Supplementary file 1_Harnessing AI for aphasia: a case report on ChatGPT's role in supporting written expression.docx by Avery K. Allen (21449492)

“…While writing aids show promise, artificial intelligence (AI) tools, such as large language models (LLMs), offer new opportunities for individuals with language-based writing challenges.…”

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

This is an additional table reporting all data recorded our experiment. by David Vagni (8060432)

This is an additional table reporting supplementary data about external injury scores. by David Vagni (8060432)

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)

Learn!Bio study: Grouping of Participants. by Katy Andrews (22311170)

“…Post pandemic, bioscience students worry about the increased living costs and are strongly in favour of a mixture of face-to-face and blended learning approaches. Our results show that bioscience students can self-report poor mental health while developing resilience, indicating tailored support can aid in developing students’ resilience. …”

School learning model dispositions data. by David A. Katz (10056006)

“…Students in virtual learning jurisdictions reported relative decreases in injury during suicide attempt(s) (OR=0.68, 95%CI = 0.52-0.88), experiencing sexual violence (OR=0.78, 95%CI = 0.67-0.91), using electronic vapor products (OR=0.81, 95%CI = 0.70-0.95), using alcohol (OR=0.84, 95%CI = 0.74-0.95), and misusing prescription opioids (OR=0.82, 95%CI = 0.72-0.94). …”

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)

Measures. by Esther Kim (2996622)

Subjects:

Descriptive statistics and correlation for study variables. by Esther Kim (2996622)

Subjects:

Means for global competence pre- and post-test scores. by Esther Kim (2996622)

Subjects:

Means for STEM competence for pre- and post-test. by Esther Kim (2996622)

Subjects:

Table 2_Identify predictive factors for the emergence of self-reported oropharyngeal dysphagia in older men and women populations: a retrospective cohort analysis.xlsx by Shuang Liu (8449)

Table 3_Identify predictive factors for the emergence of self-reported oropharyngeal dysphagia in older men and women populations: a retrospective cohort analysis.xlsx by Shuang Liu (8449)

Table 1_Identify predictive factors for the emergence of self-reported oropharyngeal dysphagia in older men and women populations: a retrospective cohort analysis.xlsx by Shuang Liu (8449)

Feature engineering. by Youli Jiang (15249070)