Aims

• • Evaluate how effectively LLMs can simulate, reproduce, or extend scientific reasoning across disciplines.
  • Provide a benchmark venue for comparing AI-generated studies with conventional scholarship.
  • Enable transparent assessment of model performance, accuracy, and limitations in research contexts.
  • Maintain an openly accessible, growing corpus of prompts, generated articles, and peer reviews to support research on authorship, evaluation, and academic integrity.

Scope

We accept prompt-based submissions from all scholarly fields, including (but not limited to):

• Engineering, Natural, and Physical Sciences
• Social Sciences, Humanities, and the Arts
• Life, Environmental, and Health/Medical Sciences
• Computational, Data, and AI Research

Each accepted submission comprises:

1. the contributor’s prompt (defining the question/task and constraints);
2. an article generated by the editorial team using documented, reproducible protocols; open peer reviews by qualified human experts (the prompt author may serve as a reviewer, with disclosure).