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 MAE value of the model after STL decomposition. by Xiangjuan Liu (618000)

The MAE value of the model under raw data. by Xiangjuan Liu (618000)

The ROC curves and AUC values of the diagnostic model. by Zhe Wu (582498)

Three error values under raw data. by Xiangjuan Liu (618000)

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.…”

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

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

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

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

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

Three error values under STL decomposition and factor analysis. by Xiangjuan Liu (618000)

MAE values under STL model and PCA principal component analysis model. by Xiangjuan Liu (618000)

Confusion Metrics: Presenting classification results on the test set. by Muhammad Zubair (728141)

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

Subjects:

Data sets for model creation and external validation. by Junichi Kushioka (12236447)

Minimal data set. by Wei Huang (36889)

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

Input parameter rankings for continuous measurements: Input parameters (P) and their corresponding influence values (E) calculated using eqn 11, displayed in decreasing order of influence for each continuous measurement set (from Set 1A to Set 4D).... by Harry Saxton (19165441)

“…<p>Input parameter rankings for continuous measurements: Input parameters (P) and their corresponding influence values (E) calculated using <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0326112#pone.0326112.e114" target="_blank">eqn 11</a>, displayed in decreasing order of influence for each continuous measurement set (from Set 1A to Set 4D). …”

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