State transition dynamics of reputation considering third-order information and multiple reputation values: by Hitoshi Yamamoto (738861)

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)

Validation of child labor measures using third-party data, households with all children in school. by Guilherme Lichand (11410286)

Candidates from the RF method. The top 25 random forest candidates ranked by mean decrease in accuracy and mean decrease in Gini Index are in the first and second columns, respecti... by Zoë Parker Cates (22184243)

Evaluation rule considering third-order information and multiple reputation values: By cluster analysis and best-fitting distribution for each distribution done on basis of BIC, re... by Hitoshi Yamamoto (738861)

Flow chart describing samples. by Rabi Joël Gansaonré (20416803)

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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)

Data set from the 2022 study. by Peter Sandøe (553063)

Interaction plot with 95% confidence intervals generated from the GAM regression model 1 in Table 2 examining initial ED SBP and management group interactions. by Randeep S. Jawa (20489181)

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)

Flow chart for inclusion and exclusion criteria. by Maleda Tefera (9025154)

“…Conversely, the likelihood of wasting decreased in children breastfeeding in their second and third year of life (AOR: 0.75; 95% CI 0.67, 0.83) and (AOR: 0.50; 95% CI 0.43, 0.60) respectively. …”

Analysis of errors of the AI model on accuracy and decision times for different tasks during the retrospective reader study. (a) by Kerol Djoumessi (21349992)

Predicted^* value of age at school entry by height-for-age z-score and child’s sex. by Rabi Joël Gansaonré (20416803)

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Predicted^* value of age at school entry by height-for-age z-score and household socioeconomic status. by Rabi Joël Gansaonré (20416803)

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Predicted^* value of age at school entry by height-for-age z-score and mother’s education. by Rabi Joël Gansaonré (20416803)

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Age at school entry, incidence of grade repetition, incidence of dropout, and baseline characteristics of participants. by Rabi Joël Gansaonré (20416803)

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Change^a in incidence of repetition [95% confidence interval]. by Rabi Joël Gansaonré (20416803)

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Predicted^* value of age at school entry by height-for-age z-score and place of residence. by Rabi Joël Gansaonré (20416803)

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