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)

Comparisons between densitometric, biochemical, and hormonal variables and bone remodeling markers of exclusive breastfeeding mothers (EBF) 15 days postpartum and the same EBF moth... by Larissa Brazolotto Ferreira (17671168)

Effects of warming and nitrogen deposition on plant species diversity. Different lowercase letters indicated that there were significant differences in different nitrogen depositio... by Xuemei Xiang (20756894)

Correlation coefficients of CO₂ residuals at CGO and MLO with ENSO indices, SOI and Niño3.4, at the same year and previous year (bold). by Roger J. Francey (22075453)

Time-based splitting strategy and forecast horizons. by Thierry Jean (20691795)

Relationship between ordinal regression and binary classification performance. by Thierry Jean (20691795)

Passive sensing data. by Thierry Jean (20691795)

“…Results also showed that metrics that do not account for imbalance (mean absolute error, accuracy) systematically overestimated performance, XGBoost models performed on par with or better than LSTM models, and a significant yet very small decrease in performance was observed as the forecast horizon expanded. …”

Surveys. by Thierry Jean (20691795)

“…Results also showed that metrics that do not account for imbalance (mean absolute error, accuracy) systematically overestimated performance, XGBoost models performed on par with or better than LSTM models, and a significant yet very small decrease in performance was observed as the forecast horizon expanded. …”

Naringenin decreases mitochondrial function. by Lauren A. Eanes (20995499)

K-means++ clustering algorithm. by Zhen Zhao (159931)

“…Firstly, recursive feature elimination using cross validation (RFECV), maximum information coefficient (MIC), and mean decrease accuracy (MDA) methods were utilized to select population distribution feature factors. …”

Mean concentrations of sum monoterpenes and single monoterpenes: α-pinene, β-pinene, myrcene, limonene, β-(E)-ocimene, and α-terpineol obtained from the 10 distillation time (DT) f... by Valtcho D. Zheljazkov (627617)

Focal female offspring production is higher on dishes where the unrelated demonstrator originates from the same (IV) population than a different (IV-bw) population. by Emily Rakosy (20939774)

Mean concentrations of sum cannabinoids, CBD, Cannabichromene, δ8-Tetrahydrocannabinol, δ9-Tetrahydrocannabinol, and other EO constituents (acid asters, ketone, alcohol) obtained f... by Valtcho D. Zheljazkov (627617)

Mean margin gap. by Mizuki Kakizawa (22574740)

Minimum, maximum, and mean horizontal and diagonal FID for the different species. Upper 95% confidence intervals were calculated from the mean. The minimum and maximum distances fo... by Estefania Velilla (22566709)

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)

Mean internal space gap. by Mizuki Kakizawa (22574740)

Graphs showing the mean maximum temperature increase at the position with the highest mean temperature increase (A) and the mean temperature increase across all probes (B) for each... by Marsel Ganeyev (21453399)