Increasing the Scale of the Mass Spectrometry Query Language Compendium with Explainable AI by Thomas V. Harwood (22117921)

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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. …”

Modelled seroprevalence estimates (coloured regions) compared with real data (black). by Keith Fraser (1868587)

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

R source code for real data applications using the proposed NURBS-based ROC estimator. by Mahmut Sami Erdoğan (22097195)

Box and whisker plot showing asymmetry index (AI) values for cheliped propodus length and height in 109 specimens of <i>Kiwa tyleri</i>. by Christopher Nicolai Roterman (20678332)

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)

The response of AI agents to changes in the neighbor’s behavior. by Jin Han (9149)

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)

Predicted distance (km) needed to achieve a correlation coefficient of at least r =  0.50 using the median-based linear regression models. by Claire Stevens (11127729)

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Boxplots created with all possible pairwise combinations of monitoring buoys in 2021 and 2022 for Pearson correlation coefficient and normalized DTW value. by Claire Stevens (11127729)

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Map of the study area. by Claire Stevens (11127729)

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Average Moran’s I (MI), Pearson correlation coefficient (r), and normalized dynamic time warping (DTW) distance for each high frequency monitoring (HFM) variable, averaged with all... by Claire Stevens (11127729)

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Linear regressions of the distance between buoys (km) and the Pearson correlation coefficient for each pairwise buoy combination for 2021 (blue) and 2022 (gray). by Claire Stevens (11127729)

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Linear regressions of the distance between buoys (km) and the normalized dynamic time warping value for each pairwise buoy combination for 2021 (blue) and 2022 (gray). by Claire Stevens (11127729)

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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)

Localization of Ferroportin and CD71 around LD-S and LD-R PV entailing the iron flux (A.i.) by Souradeepa Ghosh (14276657)

Study1_FunctionWords. by Wataru Zaitsu (16806620)

“…Furthermore, an additional comment from the survey suggested that participants primarily relied on superficial impressions based on phraseology, expression, the ends of words, conjunctions, and punctuation marks in judgments. These findings have important implications for various scenarios, including public policy, education, and marketing, where the rapid and reliable detection of AI-generated content is increasing.…”