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AI paper review, done before you submit

Proofreading, peer review, claim credibility, source quality, and tone of voice — catch reviewer-style issues in the Nubint editor and fix them before they reach your reviewers.

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Urban Green Space and Mental Health Outcomes

Urban Green Space and Mental Health Outcomes

Urban green space is closely associated with residents' mental health (Lee et al., 2024). Among residents visiting parks three or more times a week, stress went down a lot and perceived stress scores decreased by 23% and improvements in sleep quality were also observed (Park & Chen, 2025). This suggests green space accessibility should be treated as a core indicator in urban planning.

Weakly supported

The cited source only partially supports this claim. Add a source that addresses the outcome more directly.

1,247 words

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Georgia Tech
Emory University
UT Austin
Texas A&M
Seoul National University
Georgia Tech
Emory University
UT Austin
Texas A&M
Seoul National University
Georgia Tech
Emory University
UT Austin
Texas A&M
Seoul National University

Proofread

Present your findings clearly and convincingly. Proofread checks grammar, word choice, and formality against academic writing conventions and suggests edits.

Proofread

Generally sound. Some areas can better match academic conventions.

Word choiceAccept all

A lot of A majority (63%) of participants reported improvement.

Formality2

Polish your prose

Built for scholarly writing, Proofread suggests edits by category. Accept them one by one or all at once — you stay in control.

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Results in 30s

Your document is scanned and actionable suggestions appear within seconds.

Built for academia

Catches academic writing conventions and expression errors that generic grammar checkers miss.

Easy accept

Accept suggestions one by one, by category, or all together — the final call is always yours.

Peer Review

Reads your paper the way reviewers will. It inspects structure, citation integrity, and statistical reporting, then returns scores on soundness, presentation, and contribution with reviewer-style comments.

Peer Review

6 suggestions

SoundnessPresentationContribution
Document structure2
Citation integrity3
Statistical reporting1

See rejection reasons early

Get the major and minor comments a real review would raise — before you submit, while you can still fix them.

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Three-axis scores

Soundness, presentation, and contribution are each scored so you can see where the paper is weak.

Reviewer-style comments

Checks what reviewers actually flag: missing structure, citation mismatches, statistical reporting errors.

Fix before submission

Every comment comes with its location and reasoning, so you know exactly what to revise.

Claim Credibility

Catches the risk hiding behind citations. Each claim is checked against the cited paper's text to verify it is actually supported, and issues are classified as misrepresented, contradicted, or unsupported.

Claim Credibility

7 of 17 cited claims need attention.

Supported
Weakly supported2
Misrepresented1
Contradicted1
Unsupported3

Six verdicts for every claim

From fully supported to unsupported — make sure every cited claim accurately represents the literature before you submit.

Checked against sources

Claims are checked against the cited paper's full text when it is available (your library PDF or an open-access copy), and against its abstract otherwise.

Clear classification

Misrepresented, contradicted, or unsupported — each verdict shows why it was flagged and the supporting sentence from the paper.

Avoid rejection

Unverified claims are a common cause of peer review rejection. Filter them out before submission.

Source Quality

Audits your bibliography for weak spots. It flags retractions, preprints, and unverified journals — signals that weaken your research — and helps you resolve each one in your document.

Source Quality

3 preprints and 1 retracted paper found

Publication years

20162026
Retracted1
Preprint3
Unverified journal1

Your bibliography at a glance

Identify retracted papers, preprints, and unverified journals, with a publication-age distribution of your references.

Detect source risks

Automatically finds retractions, expressions of concern, and preprints that have a published version.

Understand your bibliography

See the publication-age distribution and journal verification status of your references.

Resolve immediately

Replace with the published version, find another source, or keep it intentionally.

Tone of Voice

Aligns your document's tone with academic writing conventions. It finds colloquial phrasing, heavy passive voice, and excessive hedging, then rewrites them in your field's register.

Tone of Voice

6 tone suggestions

Colloquial phrasing3
Passive voice heavy2
Excessive hedging1

The right register for your field

Check tone against a style preset or reference papers from your field, and keep it consistent across the document.

Consistent tone

Finds sections where the style drifts and evens out the whole document.

Your choice of baseline

Use a style preset or reference papers from your own field as the standard.

Expression fixes

Colloquialisms, passive overload, and over-hedging are rewritten in academic register.

Beta

Paper Source Overlap

Make sure no sentences from the papers you read survived verbatim in your AI draft. Your draft is aligned with paper text character by character to find where they overlap.

Paper Source Overlap

5 overlapping passages across 12 paragraphs

Prior work reports that this approach yields consistent gains over existing methods

Source · Nature Communications (2024)

Verbatim overlap2
Partial overlap3

Every overlap comes with its source

See which sentence overlaps which paper, side by side with the original. Decide on the spot whether to cite it or rewrite it.

Character-level alignment

Not a similarity score — it finds runs of text that match the original verbatim, so you can see the evidence yourself.

Sources shown alongside

Each overlap comes with the paper it came from, so adding the citation is one step away.

A scope you can name

Matching runs against our indexed paper corpus. It doesn't guess about anything outside it.

Beta

AI Writing Detection

See how your manuscript reads before you submit it. Every paragraph is measured for how mechanical it reads, and inside flagged paragraphs the most mechanical sentences are pinpointed.

AI Writing Detection

5 of 12 paragraphs show AI-writing traits

Likely2
Possibly3
No traits

Most mechanical sentence

1This study holds significant implications for the field.

Results are a reference. Human writing can be flagged too.

From the paragraph down to the sentence

Verdicts are made per paragraph. Open a flagged one and the sentences that read most mechanically are ranked inside it, so you can see exactly what to revise.

Paragraph verdict, sentence ranking

Only flagged paragraphs come back, and inside each one the sentences are ranked. You don't rewrite the whole manuscript.

Language-aware thresholds

The same human writing scores differently from one language to another. Each paragraph's language is detected and the threshold follows.

A reference, not a verdict

Human writing can be flagged, and not being flagged doesn't mean AI didn't write it. Results may differ from your school's or publisher's detector.

FAQ

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