Feature importance of the extracted characteristics from the simulation using Mean Decrease in Impurity (MDI). by Simon Bin Akter (17951860)

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)

“…CVLT-II ICC = 0.992; SDMT ICC = 1.000; BVMT-R ICC = 0.822–853), with minimal scoring discrepancies per test (CVLT = 1.05, SDMT = 0.05, BVMT-<i>R</i> = 1.05–1.19). …”

Enrichment values of proteins of AP-MS experiments using all subunits of the HMR complex (related to Fig 1). by Andrea Lukacs (3752956)

The 452 registrations of the 750 feature vectors after dimension reduction using the AI algorithm autoencoder, the 6 clusters obtained with the DBSCAN clustering algorithm are colo... by Gerhard Fritsch (405224)

Subjects:

The mean absolute SHAP values for all predictors. by Ali Golestani (4651399)

“…After preprocessing, 619,988 records without any missing values were used to train and compare the performance of six machine learning models including logistic regression, K-nearest neighbors, random forest, Extreme Gradient Boosting (XGBoost), Naïve Bayes, and support vector machine. …”

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)

Increasing number of samples increases the mean G_C values of all genes. by Chintan J. Joshi (5961200)

Parameter values used in simulation. by Bilal Ahmad (773365)

“…EHGR is a hybrid multi layer routing protocol for large heterogeneous sensor nodes (smart nodes, basic nodes, user handheld devices etc.) …”

An excel template to calculate novel GGT values for any given field. by Joost L. D. Nelis (8877722)

Values of all variables. by Zixun Li (19704604)

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)

Decreased MBP levels in the brain in <i>Large</i>^{<i>myd/myd</i>} mice. by Shigefumi Morioka (8893511)

“…Decreased expression levels of MBP were observed in <i>Large</i>^{<i>myd/myd</i>} mice compared with those in control mice. …”

Average production value and consumption value losses in all economic sectors for all forcing scenarios. by Nkongho Ayuketang Arreyndip (11785650)

Mean values for all subjects, and individual values for piano players and violin players. by Ai Kawasaki (12837051)

Original values for all graphs. by Bang Xiao (5794127)

All ICI p-values before and after adjustment. by Benjamin T. Newman (18397604)

“…In this study, several innovative cellular microstructural methods, as measured from magnetic resonance imaging (MRI), are combined to characterize differences between ASD and typically developing adolescent participants in a large cohort. We first examine the relationship between each metric, including microstructural measurements of axonal and intracellular diffusion and the T1w/T2w ratio. …”

All ECI p-values before and after adjustment. by Benjamin T. Newman (18397604)

“…In this study, several innovative cellular microstructural methods, as measured from magnetic resonance imaging (MRI), are combined to characterize differences between ASD and typically developing adolescent participants in a large cohort. We first examine the relationship between each metric, including microstructural measurements of axonal and intracellular diffusion and the T1w/T2w ratio. …”

All ICA p-values before and after adjustment. by Benjamin T. Newman (18397604)

“…In this study, several innovative cellular microstructural methods, as measured from magnetic resonance imaging (MRI), are combined to characterize differences between ASD and typically developing adolescent participants in a large cohort. We first examine the relationship between each metric, including microstructural measurements of axonal and intracellular diffusion and the T1w/T2w ratio. …”