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 from: Colony losses of stingless bees increase in agricultural areas, but decrease in forested areas by Malena Sibaja Leyton (18400983)

“…</p><p><br></p><p dir="ltr">The data are related to the scientific paper “Sibaja Leyton M. et al., (under review) Colony losses of stingless bees increase in agricultural areas, but decrease in forested areas”.</p><p dir="ltr">Data are available as a csv file titled:</p><p dir="ltr">"Sibaja_Leyton_et_al_Dataset_Stingless_Bee_Colony_Losses_in_Latin_America.csv".…”

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

“…<p><b>Objective:</b> To assess the feasibility, accuracy, and reliability of using ChatGPT-4.5 (early-access), a large language model (LLM), for automated scoring of Brief International Cognitive Assessment for Multiple Sclerosis (BICAMS) protocols. …”

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)

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)

Data Sheet 1_Large language models for closed-library multi-document query, test generation, and evaluation.docx by Claire Randolph (19747105)

“…Knowledge tests need to be generated on new material and existing tests revised, tracking knowledge base updates. Large Language Models (LLMs) provide a framework for artificial intelligence-assisted knowledge acquisition and continued learning. …”

Inherently interpretable deep learning framework highlights clinically relevant image regions. by Kerol Djoumessi (21349992)

The flowchart of the large model for font style transfer. by Weijia Zhu (65481)

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Penalty conversions yield large practical decreases, but robustness and generalizability of result are limited by data quality and sample selection. by Ryan J. Treves (13527735)

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)

Bidimensional High-Low Frequency (HF, LF) plane representation of the interaction among Phase and High-Low Clarity Groups_: In the Low Clarity (LC) group there was a larg... by David Vagni (8060432)

Feature engineering. by Youli Jiang (15249070)

Decrease in loss during the training process. by Muhammad Idrees (92773)

Loss of MAP4K4 expression causes a decrease in the number of neutrophils. by Guihua Wang (286390)

Machine Learning Models for High Explosive Crystal Density and Performance by Jack V. Davis (9175514)

“…The rate of discovery of new explosives with superior energy density and performance has largely stalled. Rapid property prediction through machine learning has the potential to accelerate the discovery of new molecules by screening of large numbers of molecules before they are ever synthesized. …”

<b>Supporting data for manuscript</b> "<b>Voluntary locomotion induces an early and remote hemodynamic decrease in the large cerebral veins</b>" by Kira Shaw (18796168)

“…<p dir="ltr">The CSV file 'Eyreetal_DrainingVein_SourceData' contains the averaged time series traces and extracted metrics from individual experiments used across Figures 1-5 in the manuscript "Voluntary locomotion induces an early and remote hemodynamic decrease in the large cerebral veins". The following acronyms included in the CSV file are defined as follows: Hbt is total hemoglobin, Art is artery region, DV is draining vein region, WV is whisker vein region, SEM is standard error mean, TS is time series, max peak is maximum peak, min peak is minima, AUC is area under the curve, WT is wild-type, AD is Alzheimer's disease, ATH is atherosclerosis and MIX is mixed AD/atherosclerosis. …”

Innovation and night light in large and small cities. by Saul Estrin (8629173)

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Geographical distribution of large cities and small cities. by Saul Estrin (8629173)

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Table 5_Characteristics of peripheral immune response induced by large-vessel occlusion in patients with acute ischemic stroke.xlsx by Ling Ma (107282)

“…</p>Methods<p>Here, retrospective data from AIS with large vessel occlusion (LVO) and small vessel occlusion (SVO), and healthy controls, were initially analyzed. …”