PNAS Nexus AI Policy: ChatGPT and Generative AI Disclosure Rules for PNAS Nexus Authors
PNAS Nexus (NAS) requires AI disclosure under the publisher rules. AI cannot be an author. This guide covers where to disclose, what to disclose, and the consequences of non-compliance for PNAS Nexus submissions.
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Quick answer: The PNAS Nexus AI policy follows the publisher's rules calibrated to broad-impact research submissions.
AI tools can be used for manuscript preparation but substantive generative-AI use must be disclosed in the location the publisher requires; basic copy editing may be treated differently, with PNAS Nexus's editorial team checking specifics during submission screening or review. AI cannot be listed as an author of any PNAS Nexus paper. AI-generated figures and schematics representing original research data are prohibited under PNAS Nexus's image-integrity standard.
PNAS Nexus (NAS) editors can treat undisclosed substantive AI use as a publication-ethics problem, with the response depending on the publisher policy, the timing, and whether the scientific record is affected.
Run the PNAS Nexus submission readiness check which includes an automated AI-disclosure audit, or work through this guide manually. Need broader context? See the PNAS Nexus journal overview.
The Manusights PNAS Nexus readiness scan. This guide tells you what PNAS Nexus (NAS)'s editors look for when verifying AI disclosure at desk-screen. The scan tells you whether your manuscript has the disclosure language required by the current journal policy before you submit.
We have reviewed manuscripts targeting PNAS Nexus (NAS) and peer venues; the named patterns below are patterns we check against the publisher's public AI policy and common editorial-screening risks. 60-day money-back guarantee. We do not train AI on your manuscript and delete it within 24 hours.
Editorial detail (for desk-screen calibration). Verify the current Editor-in-Chief and handling-editor list on the journal's editorial-team page before quoting any name in a submission cover letter. Submission portal: Pnas journal page. Manuscript constraints: 250-word abstract limit and 6,000-word main-text cap (PNAS Nexus flexible during peer review).
We reviewed the publisher's AI policy framework against current PNAS Nexus author guidelines (accessed 2026-05-08); evidence basis includes both publicly documented the publisher policy and our internal anonymized submission corpus. The applicable word limit at PNAS Nexus is shown below: 250-word abstract limit and 6,000-word main-text cap (PNAS Nexus flexible during peer review).
The manuscript word limit at this journal is 6,000 words for main text (verify article-type-specific caps in the latest author guidelines). The named editorial-culture quirk: PNAS Nexus academic editors emphasize reproducibility-first review with shorter desk-screen window than PNAS proper.
What does PNAS Nexus (NAS)'s AI policy require?
PNAS Nexus authors should check four policy areas under the publisher's current AI framework before submission:
Rule 1: Disclose every AI tool used in manuscript preparation
Authors should document substantive generative-AI use with the tool name, version or access date, and how it was used. Use the disclosure location specified by the current publisher policy, often Methods or a dedicated AI-use statement, rather than burying it in the cover letter. Examples that REQUIRE disclosure at PNAS Nexus:
- For PNAS Nexus-targeted manuscripts addressing broad-impact research: using ChatGPT, Claude, Gemini, or similar to draft, polish, or edit manuscript text passing through PNAS Nexus editorial review
- For PNAS Nexus submissions: using AI to generate boilerplate text for limitations, ethics statements, or PNAS Nexus-specific response-to-reviewers letters that cite the publisher's framework
- For PNAS Nexus (NAS) submissions: using AI to translate manuscript text into English from another language, with the publisher expecting disclosure of the source language and translation chain
- For PNAS Nexus literature reviews: using AI for citation discovery or summarizing prior PNAS Nexus work; the publisher's policy applies regardless of citation context
- For PNAS Nexus analytical pipelines: AI-assisted code generation requires Methods or code disclosure under the current publisher policy, particularly when code affects analysis
Examples that do NOT require AI disclosure:
- At PNAS Nexus, using grammar/spell checkers (Word) for line-level edits, when used without generative AI features for new manuscript content
- For PNAS Nexus submissions, using reference managers (Zotero, EndNote) for citation formatting against the publisher's style guide
- For PNAS Nexus (NAS) statistical analysis, using established statistical software (R, Stata, SPSS) where the algorithm is the established tool documented in PNAS Nexus's methodological norm, not a generative AI
Rule 2: AI cannot be an author
No AI tool can be listed as an author of a PNAS Nexus paper, particularly for broad-impact research-class submissions. Under the publisher's policy: authorship requires the ability to take responsibility for the content, agree to be accountable for accuracy, and to consent to publication. AI tools cannot do any of these in PNAS Nexus's editorial framework. This rule is consistent across all the publisher-published journals and applied at PNAS Nexus's desk-screen.
Rule 3: AI-generated figures are prohibited for original research data
PNAS Nexus (NAS) editorial team does not accept AI-generated images, figures, or schematics that represent original research data in broad-impact research-class submissions. AI tools may assist with figure layout (axis labeling, color schemes) but the underlying data visualization must come from the actual research. AI-generated diagrams used for conceptual illustrations (e.g., a schematic of a hypothesized mechanism) require explicit disclosure and a statement that the diagram is conceptual.
Rule 4: Disclose AI use in peer review participation
Reviewer AI-use rules are publisher-specific and can change quickly. Reviewers must follow the journal's confidentiality and AI-use policy; authors should not assume that reviewer-side AI rules are identical across journals in the same portfolio.
How does PNAS Nexus (NAS)'s AI policy compare to peer journals?
Rule | PNAS Nexus stance | the publisher default | Policy basis |
|---|---|---|---|
AI authorship | Prohibited | Prohibited | Authorship/accountability |
Disclosure location | Methods section | Methods section | Authorship/accountability |
AI-generated figures | Prohibited for original data | Prohibited | Image-integrity guidance |
Reviewer AI use | Disclosure required | Disclosure required | Peer-review confidentiality guidance |
Enforcement intensity | Desk-screen check | Desk-screen check | Submission-stage policy check |
Source: (accessed 2026-05-08) plus PNAS Nexus author guidelines.
What does AI disclosure look like in a PNAS Nexus Methods section?
Acceptable disclosure language for PNAS Nexus submissions:
"For our broad-impact research-focused manuscript at PNAS Nexus, we used ChatGPT-4o (OpenAI, version dated October 2024) to polish English-language phrasing in the Introduction and Discussion sections. We did not use generative AI for data analysis, figure generation, or substantive manuscript content. All authors reviewed and edited the AI-assisted text and take responsibility for the final manuscript."
Or, for AI-assisted code:
"For this PNAS Nexus submission addressing broad-impact research, initial Python code for the Bayesian regression analysis was drafted with Claude 3.5 Sonnet (Anthropic, version dated December 2024). All code was reviewed, modified, and validated by the authors before use; the final version is available at [repository URL]. Statistical inference was performed using the established R package brms."
What does NOT pass PNAS Nexus's desk-screen:
- For PNAS Nexus addressing broad-impact research: "AI tools were used in manuscript preparation." Too vague for the publisher editorial review of PNAS Nexus submissions; the PNAS Nexus editorial team needs the specific tool name, version, and specific use case
- "We acknowledge AI assistance in the Acknowledgments." (Do not rely on this location unless the current journal policy explicitly allows it.)
- "ChatGPT helped write this paper." (Insufficient detail on use case)
- No disclosure when AI was used (publication-ethics violation)
Desk-screen risks we see before submission
For PNAS Nexus-targeted manuscripts, the patterns below are common AI-policy risk areas to check against the publisher's current guidance before submission. Of the manuscripts we screened in 2025 targeting PNAS Nexus and peer venues, the patterns below are the same ones the journal's editorial AI committee flags during editorial review.
AI disclosure missing despite obvious AI-assisted phrasing. Substantive AI-assisted drafting without a required disclosure can trigger an editorial query. Check whether your manuscript reads as AI-assisted
AI disclosure placed in the wrong manuscript location. PNAS Nexus editorial team flags this as a common mistake against broad-impact research submissions. Publisher policies differ on whether AI disclosure belongs in Methods, a dedicated AI-use statement, acknowledgments, or another manuscript section. A misplaced disclosure can create an avoidable submission query. Check whether your AI disclosure is in the right section
Generic disclosure language without tool name and version. PNAS Nexus editorial team requires the specific tool, its version (or access date), and the specific use case. "AI tools were used" without specifics gets returned. Check whether your AI disclosure has the required specificity
What is the PNAS Nexus AI-policy compliance timeline?
Stage | Duration | What happens |
|---|---|---|
Author drafts AI disclosure | 30-60 minutes | Identify all AI use, gather tool versions, write Methods paragraph |
Co-author review of disclosure | 1-2 days | All authors confirm the disclosure is complete and accurate |
Editorial desk-screen check | 1-2 weeks | PNAS Nexus's editorial team checks the disclosure against the manuscript when policy review is triggered |
Editorial query (if disclosure incomplete) | 5-10 days | Editor requests revision before sending to peer review |
Reviewer AI-disclosure check | During peer review | Reviewers verify the disclosure matches the manuscript style |
Source: Manusights internal review of PNAS Nexus-targeted submissions, 2025 cohort.
Submit If
- For PNAS Nexus (NAS) submissions on broad-impact research: the manuscript documents substantive generative-AI use with the tool name, version or access date, specific use case, and disclosure location required by the current journal policy
- For PNAS Nexus: no AI tool is listed as an author; all listed authors meet authorship criteria and take responsibility for the final manuscript
- For PNAS Nexus (NAS): figures and schematics representing original research data come from the actual research, with any AI-assisted image or figure workflow checked against the current journal image policy
- For PNAS Nexus submissions: the disclosure makes clear that human authors reviewed the AI-assisted material and take responsibility for the final manuscript
Readiness check
Run the scan while the topic is in front of you.
See score, top issues, and journal-fit signals before you submit.
Think Twice If
- The manuscript contains substantive AI-assisted drafting but no disclosure; this can trigger an editorial query if the journal requires disclosure for that use case.
- The AI disclosure is placed in a section the current journal policy does not recognize.
- The disclosure language is generic without naming the tool, version or access date, and use case; journals may query or return manuscripts with this gap.
- Any figure, schematic, or image workflow used generative AI without being checked against the current journal image policy.
Manusights submission-corpus signal for PNAS Nexus (NAS).
Of the manuscripts our team screened before submission to PNAS Nexus and peer venues in 2025, the AI-policy compliance gap most consistent across the cohort is generic disclosure language without tool-version specificity. In our analysis of anonymized PNAS Nexus-targeted submissions, manuscripts with complete AI disclosure (tool name, version, specific use case, all-author confirmation) clear desk-screen at the same rate as manuscripts without AI use; manuscripts with incomplete or missing disclosure trigger editorial queries that add 1-2 weeks to the timeline.
PNAS Nexus (NAS) follows the publisher's public AI policy, but authors should verify the current journal page before submission because AI-use rules, disclosure locations, and image guidance continue to change.
What can PNAS Nexus authors do to stay ahead of AI policy changes?
The publisher's AI policy framework continues to evolve as 2026 brings new ICMJE recommendations, COPE guidance refinements, and journal-specific clarifications. PNAS Nexus authors targeting broad-impact research submissions should track three signals throughout 2026:
Quarterly policy updates from the publisher. the journal's editorial AI committee reviews the AI framework on a rolling basis. PNAS Nexus authors who pre-register their disclosure language at submission time tend to face fewer revisions during the 2026 transition period than authors who write boilerplate disclosures.
Field-specific clarifications for broad-impact research. Different research domains see different AI use patterns. PNAS Nexus's editorial team has been refining what counts as "substantive AI use" versus "ancillary AI assistance" for broad-impact research work. Authors who err on the side of more disclosure rather than less avoid the publication-ethics gray zone.
Reviewer disclosure norms. As the publisher extends AI-disclosure rules to peer reviewers, the response rate from PNAS Nexus reviewers may shift. Authors should expect that PNAS Nexus reviewers' use of AI tools is now also disclosed and factored into editorial decisions.
- Manusights internal preview corpus (100+ PNAS Nexus-targeted manuscripts, 2025 cohort)
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Frequently asked questions
Yes, with policy-required disclosure. PNAS Nexus (NAS) follows the publisher's current AI policy and broader publication-ethics guidance. AI tools can be used for language editing, manuscript preparation, and analysis support, but substantive generative-AI use must be disclosed in the location the publisher requires; basic copy editing may be treated differently. AI cannot be listed as an author, and human authors bear full responsibility for the content.
Use the disclosure location required by the current journal policy. For substantive generative-AI use, name the tool, version or access date, and use case, and make clear that human authors reviewed the final content. The journal may check this during submission screening, peer review, or production.
No. PNAS Nexus (NAS) prohibits AI-generated figures, schematics, and images intended to represent original research data. AI tools may assist with figure layout and labeling, but the underlying data and visualizations must come from the actual research. This rule is part of the publisher's broader image-integrity policy.
PNAS Nexus can treat undisclosed substantive AI use as a publication-ethics problem. The response depends on the publisher policy, the timing, and whether the scientific record is affected.
The shared publisher-level policy usually covers AI authorship, disclosure, and image or figure restrictions. Journal-specific guidance can differ in disclosure location, article-type expectations, and how the policy is checked during screening.
Sources
- [the publisher AI policy] (accessed 2026-05-08)
- PNAS Nexus author guidelines (accessed 2026-05-08)
- ICMJE recommendations on AI use (accessed 2026-05-08)
- COPE guidance on AI in research publication (accessed 2026-05-08)
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