
Good Publication Practice
For authors and sponsors: the principles of authorship, ethics and transparency every paper should follow.
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This special edition explores the differences between leading LLMs, their strengths and limitations, and their practical applications across scientific research, medical writing and regulatory submissions. It provides guidance on selecting, testing and using these tools responsibly while keeping scientific integrity, confidentiality and human judgement firmly at the centre.
Six things you will be able to do after reading this guide.
Why the same model behaves differently across products, and what retrieval, document handling and account tier change.
A five-question routine that separates bibliographic accuracy from whether a source actually supports the claim.
Starting points for 16 scientific tasks, from literature discovery to CSRs, protocols and submission text.
What paid tiers do and do not buy, and when a subscription removes a real bottleneck.
Consumer accounts, enterprise agreements and self-hosted models: why governance comes before convenience.
A reusable protocol and a 12-criterion scoring framework for comparing tools on your own documents.
Three quick questions taken from the guide. Test what you already know.
0of 3 correct so far
Question 1 of 3
In the first systematic study of ChatGPT citations, what share of references did GPT-3.5 fabricate?
Question 2 of 3
In a 2026 study comparing AI tools with PubMed, which general chat tool returned the fewest hallucinated citations?
Question 3 of 3
Does a paid subscription guarantee more accurate answers?
The guide covers each of these in depth, from reference checking to choosing a paid plan.
Download the free guideA few of the 27 pages, so you know exactly what you are getting.
Start with your brief and task. For drafting from source documents, ChatGPT and Claude are reasonable candidates to test; Copilot may be more convenient in Microsoft 365; DeepSeek may suit technical or cost-sensitive workflows; and Perplexity may help orient you to current sources. None should be trusted without verification. Choose the tool that performs reliably on your representative tasks under your governance requirements.
Perplexity can make source inspection easier, and the 2026 medical-search study reported fewer hallucinated citations than the other general chat tools tested. That finding is encouraging but specific to the study design and configurations. A genuine citation can still be irrelevant, incomplete or misinterpreted; always inspect the original source.
Pay when additional usage, model access, research features, context capacity, integration or organisational controls solve a real problem. Do not pay assuming a subscription guarantees correctness or comprehensiveness. Compare free and paid configurations on the same tasks and include the cost of human checking.
They can encourage over-reliance when authors focused on time-saving accept confident answers without independent engagement. Research associates confidence in AI with lower reported critical-thinking effort in some knowledge-work settings, but does not prove inevitable or permanent decline. Ask the tool to challenge your argument, check claims against evidence, and retain the ability to defend conclusions without it.
Authorship, ethics and transparency: the principles that apply whether or not AI was used.
Manuscripts, publication plans and author support, with every claim checked against its source.
CSRs, protocols, investigator brochures and submission documents prepared to agency standards.