Results 191 to 200 of about 42,825 (282)
Forget Plagiarism: It's Originality, Utility, and Contribution That Matter in Academia Now. [PDF]
Savulescu J, Schuklenk U.
europepmc +1 more source
The Plagiarist in the Machine? Generative AI and the Will to Fail
ABSTRACT This paper argues that the real challenge posed by Large Language Models (LLMs) in Higher Education lies not in their potential for plagiarism, but in their creation of a new form of writing that is indistinguishable in the traditional essay.
Matthew J. Barnard, Keith Crome
wiley +1 more source
Plagiarism - How to Use and Read it. [PDF]
Vatkar AJ, Kale S, Shyam A, Shinde S.
europepmc +1 more source
Professionals' insights on the use of large language models (LLMs) in software development. This abstract highlights how transformer‐based models enhance productivity, reduce coding time, and assist with tasks such as code generation, debugging, and documentation, while also emphasizing potential challenges including overdependence and ethical ...
Sargam Yadav +13 more
wiley +1 more source
Retraction: The Association Between Janus Kinase 2 and Factor V Leiden Mutations and Thrombotic Complications in Patients With Myeloproliferative Disorders: A Study From Saudi Arabia. [PDF]
Sayed WS +4 more
europepmc +1 more source
Making regions and revolutions: whose ‘Gulf’?
Singapore Journal of Tropical Geography, EarlyView.
Isha Panwar
wiley +1 more source
ABSTRACT Background The advent of artificial intelligence (AI) has fundamentally changed how education is delivered and how students perform. Since its launch, ChatGPT, a popular generative AI tool, has generated mixed reactions. Objectives This research systematically reviews the opportunities, perceptions, and challenges of using ChatGPT among ...
Olukayode Emmanuel Apata +2 more
wiley +1 more source
Retracted: Enhancing diagnostic accuracy in breast cancer: integrating novel machine learning approaches with enhanced image preprocessing for improved mammography analysis. [PDF]
Mehrabi M, Salek N.
europepmc +1 more source
If You Really Want to Know How AI Is Changing Peer Review Talk to Early Career Researchers
ABSTRACT The Harbingers study of early career researchers (ECRs), their work life and scholarly communications, began by studying generational—Millennial—change (H1 c.2016), then pandemic change (H2 c2020) and is now investigating yet another: artificial intelligence (H3 2024–).
David Nicholas +9 more
wiley +1 more source

