iKIR score decreases protection associated with protective class II genotypes in T1D. by Laura Mora-Bitria (20477525)

This is the data set that we used to reach the conclusions drawn in the manuscript with related metadata and methods. by Farayi Kaseke (19560197)

An illustration for the lineages identification procedure. Left panel: Each leaf represents a cell, characterized by its measured set of barcodes, denoted as . Each individual barc... by Nava Leibovich (12908477)

Minimal data set. by Wei Huang (36889)

“…Each10 units increase in BRI, ASM/ BMI decreased by 29% (β = −0.29,95% CI: −0.31, −0.28, <i><i>p</i></i> value < 0.0001). …”

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. …”

Benchmarking DFT Accuracy in Predicting O 1s Binding Energies on Metals by Elizabeth E. Happel (22391811)

Subjects:

Benchmarking DFT Accuracy in Predicting O 1s Binding Energies on Metals by Elizabeth E. Happel (22391811)

Subjects:

Setting of experimental environment and model parameters. by Guozhu Sui (21672798)

Input parameter ranking for discrete measurements: Each column displays parameters (P) and their influence values (E) calculated using Eq 11, shown in decreasing order of influence. Results are presented for progressively expanding discrete measurement sets (from Set 1 to Set 3F). Only parameters with influence values greater than 0.01 are shown. by Harry Saxton (19165441)

“…Results are presented for progressively expanding discrete measurement sets (from Set 1 to Set 3F). Only parameters with influence values greater than 0.01 are shown.…”

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

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

Comparison of WEI values for two scenarios. by Danuta Roman-Liu (8532645)

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

Kolmogorov-Smirnov (KS) test for the different parameter value pairs at a 95% confidence level. We tested the null hypothesis for all parameters: The RMSEs obtained for one pair of... by Cyrine Chenaoui (22177098)

Validation results for the different scenario parameter sets and the resulting KGE_mean value. by Fabian Mitze (21084251)

Prediction (a-d) and infusion deviation (e-f) results under different training sets and test sets. by Leijie Wang (21485157)

Subjects:

Experimental parameter information setting table. by Wenhui Wang (34265)

Diagnostic value of the 8 hub genes in the GSE52093 dataset. by Wei He (131453)

Set-up of the optimized 90:20 Isometric Posterior Chain Test. by Dominic Michael Rasp (19959412)

Table 1_Food scarcity and decrease in income are associated with depression after COVID-19 pandemic in rural settings.docx by Dharmendra Gahwai (20987825)