Reviewer3

Multi-agent peer review trusted by thousands of researchers.

[Reviewer3 @Reviewer3]

My department's new 'publish or perish' motto has been simplified to just 'perish,' for clarity and efficiency.

[Yin lab @HenryYin19]

I think our experience with publishing this paper actually illustrates why the current publication system is broken. We had nearly the smoothest possible experience, from Nature to Nature Neuroscience we had the same reviewers who were professional and fair. We didn't have any problems at all but the whole process still took a year and a half. Often this type of paper can take 3 years to publish.

[Reviewer3 @Reviewer3]

Lab work requires meticulous attention to detail; one wrong pipetting technique, and you've accidentally created a self-aware slime mold that now controls the lab's Wi-Fi.

[Reviewer3 @Reviewer3]

We just released this consistency check into our core review flow. It will catch the big and little inconsistencies. And as always, you can filter comments by severity depending on how much detail you want.
Read more: https://t.co/GawG9js79A

[Reviewer3 @Reviewer3]

We built a manuscript consistency check to catch places where a paper contradicts itself.

Found some interesting stuff when we tested it on a highly cited 2020 Nature Medicine paper on COVID-19 transmission dynamics.

[Reviewer3 @Reviewer3]

It also found a discrepancy between the reported R version in the Methods section and the Reporting Summary!

[Reviewer3 @Reviewer3]

Reviewer 3 suggested adding a 'foundational' paper to my bibliography, which turned out to be their own 2023 undergraduate thesis.

[Hayashi Heikichi @lianda_edu]

just use Reviewer3！@reviewer3

[Reviewer3 @Reviewer3]

Applying for an academic job feels a lot like entering a lottery, except you pay the organizers for the privilege and the prize is just more work.

[Reviewer3 @Reviewer3]

9 other issues found here: https://t.co/lhnpa2hyYv

[Reviewer3 @Reviewer3]

A new Nature Medicine paper claims that frontier models (GPT 5.2, Gemini 3.1 Pro, Opus 4.6) now outperform clinical AI like @EvidenceOpen across multiple medical benchmarks.

I looked into it further with Reviewer3 and it has a few flaws that undermine its major conclusions:

[Reviewer3 @Reviewer3]

If you work in medicine or use OpenEvidence, how does it compare with frontier models? Do you trust benchmark results like these?

[Natalie Khalil @natalienkhalil]

@EvidenceOpen Also near negligible agreement between the human evaluators (described as "fair" in the paper) and potential self-preference bias in the LLM evaluators

https://t.co/PiG0ErZLxP

[Reviewer3 @Reviewer3]

Congrats! You’ve just completed the seventh round of revisions. Just one more round and then we’ll let you know if your paper has been accepted.