Reviewer-grade feedback
in 10 minutes
Deep mathematical review with suggested fixes on every issue. Catches subtle errors like normalization gaps, Cauchy-Schwarz misapplications, and compensating errors — with reasoning you can follow.
Currently optimized for mathematics papers. Support for other fields coming soon.
5 credits per section — analyze the whole paper or specific sections.
Uses credits from your ScienceStack subscription. Free tier includes 30 credits/month.
Deep analysis with actionable fixes
Every issue includes reasoning, exact citations, and a suggested fix. Written in a collaborative tone — like feedback from a helpful colleague.
Heat normalization missing
Section 2.3“The heat kernel satisfies...”
The normalization constant doesn't match the standard heat kernel formula. The integral should equal 1, but the stated form integrates to (4πt)^{n/2}. This propagates to Theorem 3.1.
Add the normalization factor (4πt)^{-n/2} to the kernel definition.
Jacobian error in change of variables
Section 4.2“det(J) = r^{n-1}...”
The Jacobian determinant has an error in the exponent. Should be r^{n-1} sin^{n-2}(θ₁)... not r^{n}. However, the final answer appears correct — this may be a compensating error.
Verify the Jacobian calculation; the result may be correct despite the intermediate step.
Complex-valued inequality not well-defined
Section 3.1“g^{1/4}(a_m) ≥ |⋯|”
g^{1/4}(a_m) is a priori complex-valued, so writing an inequality like g^{1/4}(a_m) ≥ ... is not meaningful without taking absolute values or restricting to real arguments.
Replace the inequality by one for absolute values, or add assumption that g is real-valued.
Issues appear as clickable annotations on your paper — jump directly to the problem.
How it works
Upload or open any paper, click “Generate Referee Report”, and get comprehensive feedback in minutes.
Deep Mathematical Analysis
Catches subtle issues like Cauchy-Schwarz misapplications, normalization gaps, and covariance problems that surface-level review misses
Suggested Fixes
Every issue includes an actionable suggestedFix — not just what's wrong, but how to address it
Compensating Error Detection
Recognizes when errors cancel out and the final answer is still correct — avoiding false positives
Collaborative Tone
"I initially stumbled at..." — feedback written like a helpful colleague, not a harsh critic
Reasoning Journey
Shows the confusion and resolution process, so you understand exactly why something was flagged
Better Signal-to-Noise
Filters raw issues down to the ones that matter — fewer false alarms, more real problems
Why we're different
Most AI review tools give surface-level feedback. We built something deeper.
| Feature | Us | Others |
|---|---|---|
Suggested fix on every issue Actionable recommendations, not just problem identification | ✓ | ✗ |
Collaborative tone "I initially stumbled at..." instead of terse criticism | ✓ | ✗ |
Compensating error detection Recognizes when errors cancel out and final answer is correct | ✓ | ✗ |
Reasoning journey Shows the confusion → resolution process | ✓ | ✗ |
Better signal-to-noise Filters raw issues to surface real problems | ✓ | ✗ |
Catches subtle math errors Normalization gaps, covariance issues, summability problems | ✓ | Partial |
What you get
Comprehensive feedback designed to catch issues before reviewers do.
| Turnaround time | ~10 minutes |
| Suggested fix on every issue | Actionable, not just diagnostic |
| Collaborative tone | "I initially stumbled...", "What I checked..." |
| Compensating error detection | Knows when final answer is still correct |
| Reasoning journey | Shows confusion → resolution process |
| Better filtering | Fewer false positives, more real issues |
Iterate on your drafts as many times as you need before submission.
Simple credit-based pricing
Referee reports use credits from your ScienceStack account.
Per section analyzed
- Analyze whole paper or specific sections
- Only critical & significant issues reported
- Inline annotations on your paper
- Exact text citations
- Suggested fixes on every issue
Frequently Asked Questions
Ready to improve your paper?
Upload your paper to your library, then use /math_review in the chat to generate a referee report.