Reference Checks for
Editorial Review.

A pre-publication check on a manuscript's reference list — run per submission, as part of your normal review process. Every citation gets checked against 7 academic databases and comes back Verified, Mismatch, or Hallucinated, with a real replacement suggested when something doesn't check out.

Why One Database Isn't Enough

A single database lookup has a specific failure mode: a fabricated or duplicate DOI can happily resolve inside one provider's records even when the citation is wrong, because that provider indexed the bad entry too. Trusting whichever database answers first means trusting whichever database is wrong.

AccuraCite queries OpenAlex, Crossref, Semantic Scholar, PubMed, DBLP, arXiv, and CORE for every reference and looks for independent agreement across them, rather than accepting the first hit. A citation is marked Verified only when multiple independent sources agree on it — which is specifically what makes the check resistant to a single bad or duplicate DOI entry sitting in any one database.

That handles whether a paper exists. It doesn't handle whether it says what the manuscript claims it says — so for every candidate match, AccuraCite also pulls the source's abstract and checks that it actually supports the citation, not just that the title and author string line up. A real paper cited for the wrong claim is still flagged.

What a Report Looks Like

Below is an illustrative excerpt — 9 of 32 references from a hypothetical submitted manuscript — showing the mix of results a real reference list typically produces. Most citations verify cleanly; a small number get flagged, and each flag comes with the reason.

Manuscript #2026-0114 — Reference List

Showing 9 of 32 citations (illustrative example)

6 Verified 2 Mismatch 1 Hallucinated

Ferreira, T., & Nakamura, H. (2021). Attention bottlenecks in multimodal transformers. Advances in Neural Information Processing Systems, 34, 8891–8903.

Verified

Matched on OpenAlex, Crossref, and Semantic Scholar; abstract confirms the claim it's cited for.

Patel, S. (2019). Longitudinal effects of sleep fragmentation on working memory. Journal of Cognitive Neuroscience, 31(4), 512–529.

Verified

Matched on Crossref and PubMed.

Kowalski, M., Lindqvist, A., & Osei, B. (2020). Federated learning under non-IID data: A survey. IEEE Transactions on Neural Networks and Learning Systems.

Mismatch

Title and authors match a real paper — but it published in 2022, not 2020, and the DOI in the manuscript points to an unrelated article. Suggested replacement: the correctly dated 2022 record.

Chen, L. (2018). Microbiome diversity and host immune response in zebrafish. Cell Reports, 24(3), 601–612.

Verified

Matched on Crossref, PubMed, and OpenAlex.

Alvarez, R., & Kim, J. (2023). Scaling laws for instruction-tuned language models. arXiv:2301.04567.

Verified

Matched on arXiv and Semantic Scholar.

Whitfield, D. (2017). A unified theory of catalytic asymmetric synthesis. Journal of the American Chemical Society.

Hallucinated

No record across any of the 7 databases — this author, title, and venue combination doesn't correspond to any indexed publication. A closest-match real paper is suggested for the authors to confirm or correct.

Brandt, S., & Okafor, C. (2022). Carbon sequestration potential of urban green infrastructure. Environmental Science & Policy, 128, 45–56.

Verified

Matched on Crossref and OpenAlex; abstract confirms the sequestration claim cited.

Liu, Y. (2020). Deep reinforcement learning for traffic signal control. Transportation Research Part C.

Mismatch

The DOI listed in the manuscript resolves to a different, unrelated 2015 conference paper — a duplicate/fabricated DOI, the exact case cross-provider consensus is built to catch. The title exists in the record, but under a different DOI.

Suzuki, N., Mehta, R., & Dubois, P. (2021). Placebo response rates in randomized trials for chronic pain: A meta-analysis. Pain Medicine, 22(6), 1301–1314.

Verified

Matched on PubMed, Crossref, and Semantic Scholar.

Fitting It Into Rolling Review

This is built to run per manuscript, when it needs to — not as a one-time audit of everything a journal has ever published.

  1. 1 A manuscript comes up for review. Paste its reference list, or a BibTeX/RIS export, directly into the checker for a quick pass. Uploading the manuscript PDF itself requires the Pro or Bulk plan.
  2. 2 Every citation is checked against the 7 databases with cross-provider consensus and abstract-level matching, as described above.
  3. 3 The report comes back per manuscript — Verified, Mismatch, or Hallucinated for each reference, with a suggested real replacement wherever something doesn't check out.
  4. 4 You decide what a flag means in context — same as any other issue you'd send back to authors before or during review. The check doesn't make that call for you.
  5. 5 Handling several submissions in the same week? The Bulk Verification plan scans up to 30 PDFs in one job — enough for that week's batch of incoming manuscripts, not a full backlog sweep.

Frequently Asked Questions

Does this replace peer review or editorial judgment?

No. It checks whether a citation exists, matches its stated metadata, and is topically supported by its abstract. It doesn't evaluate methodology, novelty, or whether the manuscript's argument holds up — that's still on you and your reviewers.

Is our data safe if we upload unpublished manuscripts?

PDF files aren't permanently stored — they're processed for the verification job and discarded once it completes. To check each reference, we send the citation metadata (titles, authors, DOIs) to public academic databases like Crossref and PubMed, the same information already visible in the citation itself. See the Privacy Policy for full detail.

Can we run this against our whole backlog or archive?

The Bulk Verification plan scans up to 30 PDFs per job — sized for a batch of the week's incoming submissions, not a full-journal audit. It's built to run per-manuscript as part of your normal rolling review, not as a one-time sweep of everything you've ever published.

How do we set this up for our editorial team?

There's no dedicated institutional plan yet. Individual editors can use the Bulk Verification plan directly, and if you want to talk through how it would fit your review process, contact us.

Have questions about using this for your journal or editorial team?

Tell us how your review process works and we'll tell you honestly whether this fits.

Want the mechanics in more detail first? Read how AccuraCite works.