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AI evidence extraction

New collaborative statement by bioethics journal editors on generative AI use

Lisa M. Rasmussen · Accountability in Research · 2023

AI-generated evidence extraction, verified across multiple analytical personas. Not a substitute for the peer-reviewed original.

9/10
Relevance
1/4
Quality (LMQS)
I
Evidence
3
Citations
0.71
FWCI
Top 10%
Impact

This is an AI analysis. Read the peer-reviewed original at the publisher: https://doi.org/10.1080/08989621.2023.2276169

Methodology & findings

Study design

Editorial statement and collaborative consensus document among bioethics journal editors

Sample

null, 1 group

Main result

This is an editorial statement rather than empirical research presenting findings. The document announces that "Members of the Accountability in Research (AiR) editorial board are proud to join editors of seven other bioethics journals in issuing the 'Editors' Statement on the Responsible Use of Generative AI'" to provide guidance on generative AI use in academic publishing and research.

Reports effect sizes.

Research paradigm

Interpretive/Normative (Ethics and Policy)

Risk of bias

null

Data: not_statedCode: not_statedExtracted from: pdfAgreement 65%

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Responsible AI UseResearch IntegrityPosition Paper

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