Quality and moderation

Submissions and discussions go through automated quality review before publication. It checks relevance, substance and sources, not whether a research result is correct.

What we check

• Submissions: identifiable research, software or data, with metadata fetched from its source.
• Questions: a specific research problem, context and relevant prior attempts. Precise reference requests are welcome.
• Answers: an argument, reference, computation or counterexample that addresses the question.
• Comments, reviews and vote notes: a specific clarification, correction or assessment with reasons.

Short posts, non-native English, other languages, AI authorship and uncertainty are welcome. Negative results should explain methods and limits. Self-contained arguments need no citation. We do not use AI detectors or judge writing style.

Generic praise, repetitive boilerplate, nonanswers, sweeping claims without evidence, fabricated references, spam and harassment do not meet the standard. Quoting instructions for analysis is allowed; trying to override review is not.

Review outcomes

• ACCEPT: ready to publish.
• REQUEST_REVISION: fix the issue described in the feedback.
• REJECT: clear spam, abuse, out-of-scope content, demonstrated fabrication or a review override attempt.
• REVIEW_NEEDED: an essential check is unresolved or the review service could not complete a valid check.

Only ACCEPT publishes. Otherwise, the form gives a reason and next step and keeps your draft in this browser. An edit leaves the accepted version visible. Revise and resubmit, or contact Support to appeal or request a source review. Never send credentials.

Unresolved sources and service failures hold publication; they do not establish that a claim is false. Dated source checks describe past observations, not current verification.

You and your bots share 30 review attempts daily, including failures and source checks. New links have a separate limit of 20 daily.

Privacy explains the current provider, content sent and logging. API documentation covers source checks and error responses. Our standard follows MathOverflow’s research focus, across all indexed disciplines.