Additional file 3 of B2M or CIITA knockdown decreased the alloimmune response of dental pulp stem cells: an in vitro study by Mingxin Hu (8630814)

Transition probabilities and class sizes for three-step LTA model (N = 432). by Carolin Oetzmann (11397968)

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. …”

The ROC of LR for three classes. by Mohammadreza Namdar (22439057)

The ROC of MNB for three classes. by Mohammadreza Namdar (22439057)

The ROC of SVM for three classes. by Mohammadreza Namdar (22439057)

The ROC of RF for three classes. by Mohammadreza Namdar (22439057)

The ROC of GNB for three classes. by Mohammadreza Namdar (22439057)

Number of primary school classes, 2013−2022. by Zhankun Han (20529082)

“…Rural elementary schools in China are scattered, the distribution rate of aesthetic education resources is low, and it is difficult to popularize high-quality aesthetic education resources. (2) The number of classes in China’s rural elementary schools decreased 30.28% from 1.139 million in 2013 to 788,000 in 2022. …”

(A) Digital designing of premolar to decrease 1 mm of root surface, (B) 3D printed tooth compared to artificial tooth of model. by Samar S. Alaghbari (21863491)

Effect of class imbalance on predictive performance. by Thierry Jean (20691795)

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

State variables before and after optimization of (Case-III). by Azhar Iqbal Kashif Butt (17290686)

State variables before and after optimization for Case-III. by Azhar Iqbal Kashif Butt (17290686)

Class-wise performance on the test set. by Muhammad Zubair (728141)

“…It is found that the experiment results provide promising classification performance for three classes – Alzheimer’s Disease (AD), Mild Cognitive Impairment (MCI) and Cognitively Normal (CN) with an overall accuracy of 97.78% ± 0.54%, precision of 97.18% ± 1.14% (AD), 97.78% ± 0.29% (CN) and 97.03% ± 1.10% (MCI), recall of 97.90% ± 0.77% (AD), 97.49% ± 1.34% (CN) and 97.25% ± 0.99% (MCI), and F1 score of 97.74% ± 0.63% (AD), 97.78% ± 0.79% (CN), and 97.54% ± 0.69%(MCI). …”

<i>Tillandsia utriculata</i> death rate data by size class. by Alexandra M. Campbell (3284094)

Distribution of SNPs and their frequencies based on mutation classes. by Sadia Afrin Runa (22504971)

Association of different trajectory classes with 30-day mortality in AMI patients with DM. by Bowen Deng (3123237)

Subjects:

Definition of LULC classes. by Firdissa Sadeta Tiye (21222102)

Association of different trajectory classes with 30-day mortality in subgroups of age, AMI types, and gender. by Bowen Deng (3123237)

Subjects: