# PeerGenius.ai - Complete Documentation

> Expert pre-submission manuscript review for researchers and academics

---

## Table of Contents

1. [Overview](#overview)
2. [Pricing Plans](#pricing-plans)
3. [Which Tier Should You Choose?](#which-tier-should-you-choose)
4. [Review Panel](#review-panel)
5. [What Each Reviewer Looks For](#what-each-reviewer-looks-for)
6. [Extended Thinking Capabilities](#extended-thinking-capabilities)
7. [Use Cases by Academic Field](#use-cases-by-academic-field)
8. [How It Works](#how-it-works)
9. [Sample Review Output Structure](#sample-review-output-structure)
10. [Handling Large Manuscripts](#handling-large-manuscripts)
11. [Supported File Types](#supported-file-types)
12. [Data Security & Privacy](#data-security--privacy)
13. [Limitations & What We Don't Do](#limitations--what-we-dont-do)
14. [Frequently Asked Questions](#frequently-asked-questions)
15. [Troubleshooting](#troubleshooting)
16. [Institutional Plans](#institutional-plans)
17. [Contact Information](#contact-information)

---

## Overview

PeerGenius.ai is an expert pre-submission manuscript review service that provides comprehensive feedback on journal papers, dissertations, theses, conference papers, preprints, and other scholarly manuscripts. Our panel of 7 specialist reviewers analyzes your work from multiple perspectives: methodology, statistics, domain relevance, argumentation, and writing quality. We deliver detailed feedback in minutes rather than weeks.

### Why PeerGenius.ai?

- **Speed**: Get reviews in 5-15 minutes instead of weeks or months
- **Validated Objectivity**: Reviewers validated against peer reviewers from a top-tier journal, delivering consistent feedback
- **Comprehensive**: Multiple perspectives from specialized reviewers
- **Actionable**: Specific suggestions with code examples where relevant
- **Multi-Model Ensemble**: Uses 4 frontier AI models (Claude Opus 4.5, Claude Sonnet 4.5, GPT-5, Gemini 2.5 Pro). Each agent uses the model best suited to its task
- **Affordable**: Dynamic pricing based on manuscript length, from $4.54 (Standard) for a typical paper

---

## Pricing Plans

Prices are dynamic, based on manuscript length. Example prices shown are for a typical 3,500-word research article.

### Individual Reviewers - Starting $1.33/agent
- Choose any combination of specialist reviewers
- Build a custom review panel
- Full detailed analysis per reviewer
- PDF export included

### Standard Tier - From $4.54 (Most Popular)
- 4 specialist reviewers working in parallel
- Domain Expert, Adversarial Skeptic, Statistical Methods, Results Accuracy
- Complete methodology analysis
- Statistical methods analysis with corrective code
- Results accuracy checking
- PDF export included

### Premier Tier - From $8.14 (Best Value)
- All 7 specialist reviewers
- Editor-in-Chief consolidation with unified decision letter
- Comprehensive editorial letter with publication decision
- Priority processing
- PDF export included

---

## Which Tier Should You Choose?

| Your Situation | Recommended Tier | Why |
|----------------|-----------------|-----|
| Quick quality check before submission | Individual (starting $1.33) | Fast feedback on major issues |
| Need statistical analysis only | Individual (starting $1.33) | Statistical Methods Expert provides deep analysis |
| Preparing for journal submission | Standard (from $4.54) | Comprehensive coverage of common reviewer concerns |
| Revising after desk rejection | Standard (from $4.54) | Identifies issues that led to rejection |
| High-stakes publication (top journal) | Premier (from $8.14) | Maximum coverage, editorial decision letter |
| Dissertation or thesis chapter | Premier (from $8.14) | Comprehensive feedback from all perspectives |
| Need editorial decision letter | Premier (from $8.14) | Only tier with Editor-in-Chief consolidation |
| Grant proposal or fellowship application | Not recommended | See limitations section |

---

## Review Panel

### Domain Expert
**Focus**: Field-specific knowledge, literature context, and novelty assessment
**Capabilities**:
- Evaluates contribution to the field
- Assesses literature coverage and gaps
- Identifies missing key references
- Evaluates novelty and significance
- Compares to state-of-the-art
- Assesses impact potential

### Adversarial Skeptic
**Focus**: Challenges assumptions, identifies logical gaps, tests conclusions
**Capabilities**:
- Questions methodology choices
- Identifies alternative explanations
- Tests logical consistency
- Highlights potential weaknesses
- Evaluates claim strength
- Checks for overgeneralization

### Statistical Methods Expert
**Focus**: Deep statistical analysis with corrective code
**Capabilities**:
- Analyzes statistical approaches and appropriateness
- Evaluates sample sizes and statistical power
- Assesses effect sizes and confidence intervals
- Identifies issues with statistical tests
- Provides R/Python correction code examples
- Reviews assumption checking
- Evaluates multiple comparison handling

### Results Accuracy Checker
**Focus**: Verifies calculations, data consistency, and result reporting
**Capabilities**:
- Cross-checks reported statistics with methods
- Verifies internal data consistency
- Checks for transcription errors
- Validates result interpretation
- Identifies discrepancies between text and tables
- Reviews figure-text consistency

### Systematic Reviewer
**Focus**: Methodology, statistics, reporting standards
**Capabilities**:
- Evaluates research design appropriateness
- Checks reporting completeness (CONSORT, STROBE, etc.)
- Assesses reproducibility
- Reviews methodology rigor
- Identifies missing methods details
- Evaluates bias and limitations discussion

### Pragmatic Reviewer
**Focus**: Clarity, practical significance, accessibility
**Capabilities**:
- Evaluates writing clarity and flow
- Assesses practical implications
- Checks accessibility for target audience
- Suggests communication improvements
- Reviews abstract effectiveness
- Evaluates figure and table clarity

### Scientific & Technical Writer
**Focus**: Technical writing, style refinement, scientific rigor
**Capabilities**:
- Improves scientific clarity and precision
- Checks terminology consistency
- Evaluates adherence to style guidelines
- Reviews computational methods
- Ensures effective communication of findings
- Identifies technical oversights

### Editor-in-Chief (Premier tier only)
**Focus**: Synthesizes all feedback into unified decision letter
**Capabilities**:
- Consolidates all reviewer feedback
- Provides overall quality assessment
- Issues editorial decision (Accept/Minor Revision/Major Revision/Reject)
- Creates comprehensive decision letter
- Prioritizes required changes
- Balances competing reviewer perspectives

---

## What Each Reviewer Looks For

### Domain Expert Checklist
- [ ] Is the research question novel and significant?
- [ ] Are key references cited appropriately?
- [ ] Is the contribution clearly articulated?
- [ ] Does the work advance the field?
- [ ] Are claims supported by the literature?

### Adversarial Skeptic Checklist
- [ ] Are assumptions clearly stated and justified?
- [ ] Could alternative explanations account for results?
- [ ] Are conclusions appropriately cautious?
- [ ] Are limitations adequately discussed?
- [ ] Is there evidence of cherry-picking?

### Statistical Methods Expert Checklist
- [ ] Are statistical tests appropriate for the data?
- [ ] Is sample size adequate and justified?
- [ ] Are effect sizes and confidence intervals reported?
- [ ] Are multiple comparisons properly handled?
- [ ] Are assumptions tested and met?

### Results Accuracy Checker Checklist
- [ ] Do numbers in text match tables/figures?
- [ ] Are calculations internally consistent?
- [ ] Are results correctly interpreted?
- [ ] Are units correct throughout?
- [ ] Do summaries match detailed results?

---

## Extended Reasoning Capabilities

Our reviewers use **extended reasoning** technology, which means they spend more time thinking through complex issues before providing feedback. This results in:

- **Deeper Analysis**: More thorough examination of methodology and logic
- **Better Statistical Verification**: More accurate identification of statistical issues
- **Nuanced Feedback**: Understanding of discipline-specific context
- **Code Generation**: Working R/Python/Stata examples for statistical corrections

Extended reasoning is enabled for all specialist reviewers, allowing deeper analysis of your manuscript from each perspective.

---

## Use Cases by Academic Field

### STEM Fields (Physics, Chemistry, Engineering, Computer Science)
**Best suited tiers**: Standard or Premier
**Key reviewers**: Statistical Methods Expert, Results Accuracy Checker, Scientific & Technical Writer
**What to expect**:
- Rigorous statistical analysis with corrective code
- Technical accuracy checking
- Methodology reproducibility assessment
- Computational methods evaluation

### Biological and Life Sciences
**Best suited tiers**: Standard or Premier
**Key reviewers**: Statistical Methods Expert, Systematic Reviewer, Results Accuracy Checker
**What to expect**:
- Sample size and power analysis
- CONSORT/ARRIVE guideline checking
- Data consistency verification
- Experimental design evaluation

### Social Sciences (Psychology, Sociology, Economics)
**Best suited tiers**: Standard or Premier
**Key reviewers**: Adversarial Skeptic, Statistical Methods Expert, Pragmatic Reviewer
**What to expect**:
- Research design validity assessment
- Statistical appropriateness checking
- Alternative explanation identification
- Generalizability evaluation

### Humanities (History, Philosophy, Literature)
**Best suited tiers**: Individual reviewers (from $1.33/agent) or Standard (from $4.54 / 4 agents)
**Key reviewers**: Domain Expert, Adversarial Skeptic, Pragmatic Reviewer
**What to expect**:
- Argumentation strength assessment
- Literature coverage evaluation
- Writing clarity feedback
- Thesis support analysis

### Medicine and Clinical Research
**Best suited tiers**: Premier (recommended)
**Key reviewers**: All reviewers valuable
**What to expect**:
- CONSORT/STROBE guideline checking
- Statistical rigor analysis with corrective code
- Results accuracy verification
- Clinical significance assessment

### Data Science and Machine Learning
**Best suited tiers**: Standard or Premier
**Key reviewers**: Scientific & Technical Writer, Statistical Methods Expert, Adversarial Skeptic
**What to expect**:
- Model validation assessment
- Baseline comparison evaluation
- Reproducibility checking
- Overfitting/generalization analysis

---

## How It Works

### Product Demo
Watch our product demo video on the homepage to see PeerGenius review a real manuscript from upload to detailed feedback: https://peergenius.ai

### Step 1: Upload Your Manuscript
Submit your PDF or DOCX manuscript along with any figures, tables, or supplementary materials.

**Automatic processing includes**:
- Text extraction from PDF/DOCX
- Figure and table identification
- Equation extraction
- Reference parsing

### Step 2: Choose Your Review Tier
Select individual reviewers, Standard (4 reviewers), or Premier (7 reviewers + Editor). Prices are based on your manuscript's length.

**Processing times**:
- Individual: 3-5 minutes per reviewer
- Standard: 5-10 minutes
- Premier: 10-15 minutes

### Step 3: Specialist Reviewers Analyze Your Work
Our specialist reviewers work in parallel, each examining your manuscript from a different perspective.

**Each reviewer provides**:
- Overall score (0-100)
- Summary of key findings
- Strengths identified
- Concerns and issues
- Specific recommendations
- Confidence level in assessment

### Step 4: Get Actionable Feedback
Receive detailed reviews with specific strengths, concerns, and suggestions.

**Premier tier additionally includes**:
- Editor-in-Chief consolidation
- Unified decision letter
- Prioritized revision list
- Publication recommendation

---

## Sample Review Output Structure

### Individual Reviewer Report

```
## [Reviewer Name] Review

### Overall Score: 75/100

### Summary
[2-3 sentence overview of the manuscript and key findings]

### Strengths
1. [Strength 1 with specific reference to manuscript]
2. [Strength 2 with specific reference to manuscript]
3. [Strength 3 with specific reference to manuscript]

### Concerns
1. **Major**: [Concern description with location and suggestion]
2. **Major**: [Concern description with location and suggestion]
3. **Minor**: [Concern description with location and suggestion]

### Specific Recommendations
- [Actionable recommendation 1]
- [Actionable recommendation 2]
- [Actionable recommendation 3]

### Confidence Level: High/Medium/Low
[Explanation of confidence in this assessment]
```

### Statistical Methods Expert Example (includes code)

```
## Statistical Methods Review

### Issue Identified: Inappropriate use of t-test with non-normal data

**Location**: Results section, paragraph 3

**Problem**: The t-test assumes normally distributed data, but Figure 2
shows clear right skew in the outcome variable.

**Suggested Correction**:

```r
# R code for non-parametric alternative
wilcox.test(treatment_group, control_group,
            alternative = "two.sided",
            conf.int = TRUE)
```

```python
# Python equivalent
from scipy.stats import mannwhitneyu
stat, p_value = mannwhitneyu(treatment_group, control_group,
                              alternative='two-sided')
```
```

### Editor-in-Chief Decision Letter (Premier tier)

```
## Editorial Decision

### Recommendation: Major Revision

Dear Author(s),

Thank you for submitting your manuscript to our review service.
After careful evaluation by our panel of specialist reviewers, we have
reached the following decision.

### Decision Summary
Your manuscript presents [summary of contribution]. However,
several issues must be addressed before the work is ready for
publication.

### Required Changes
1. [Major change 1 - consolidated from multiple reviewers]
2. [Major change 2 - consolidated from multiple reviewers]
3. [Major change 3 - consolidated from multiple reviewers]

### Suggested Improvements
1. [Minor improvement 1]
2. [Minor improvement 2]

### Reviewer Agreement
- Domain Expert: Major Revision
- Statistical Methods: Major Revision
- Adversarial Skeptic: Major Revision
- Pragmatic Reviewer: Minor Revision

We believe that addressing these points will significantly
strengthen your manuscript.

Best regards,
Editor-in-Chief
```

---

## Handling Large Manuscripts

### Document Length Limits
- **Optimal**: Up to 15,000 words (~30 pages)
- **Supported**: Up to 50,000 words (~100 pages)
- **Large documents**: Automatically processed in chunks

### How Chunking Works
For manuscripts exceeding 150,000 characters:
1. Document is divided into logical sections
2. Each section is analyzed with full context
3. Results are consolidated into unified feedback
4. Cross-references between sections are maintained

### Recommendations for Long Documents
- **Dissertations**: Submit individual chapters for best results
- **Long manuscripts**: Consider Standard or Premier for comprehensive coverage
- **Supplementary materials**: Upload separately for dedicated analysis

---

## Supported File Types

### Manuscripts
- **PDF** (Portable Document Format) - Recommended
- **DOCX** (Microsoft Word)
- Maximum size: 10MB per file

### Supplementary Materials
- **Images**: PNG, JPEG, TIFF, GIF (for figures)
- **Tables**: CSV, Excel (.xlsx, .xls)
- **Maximum**: 50 files total per review (combined across the Documents, Figures, and Tables zones)

### Figure and Table Naming
For best results, name your files descriptively:
- `Figure_1_Results_Overview.png`
- `Table_2_Demographics.csv`

Our system uses filenames to provide context to reviewers.

---

## Data Security & Privacy

### Automatic Deletion
All uploaded manuscripts and generated reviews are **automatically deleted after 30 days**. This ensures your research remains confidential and is not retained longer than necessary.

### No AI Training
We do **NOT** use your manuscripts to train our AI models. Your documents are processed by third-party AI providers (Anthropic, OpenAI, Google) solely to generate your review. These providers also do not use API-submitted data for model training.

### Encryption
- Data encrypted in transit (HTTPS/TLS 1.3)
- Encryption at rest for all stored documents
- Secure authentication through Firebase Auth

### Payment Security
Payment processing is handled by Stripe (PCI-DSS compliant). We never store your credit card information.

### Access Control
- Only you can access your reviews
- No sharing with third parties
- No access by PeerGenius.ai staff without explicit permission

---

## Limitations & What We Don't Do

### What We Don't Do
- ❌ Replace journal peer review (we complement it)
- ❌ Submit manuscripts to journals on your behalf
- ❌ Guarantee publication acceptance
- ❌ Review grant proposals or funding applications
- ❌ Verify experimental data or lab procedures
- ❌ Provide plagiarism checking (use dedicated tools)
- ❌ Review in languages other than English (limited support)
- ❌ Provide legal or ethical compliance verification

### Known Limitations
- Best results with English-language manuscripts
- Statistical verification based on reported values only
- Cannot verify raw data accuracy
- Domain expertise varies by field specificity
- May not catch all issues a human expert would find

### When to Seek Human Review Instead
- Highly specialized niche topics
- Manuscripts with significant non-English content
- Work requiring institutional ethics review
- Legal or regulatory compliance checking
- Final pre-submission check for top-tier journals (use both)

---

## Frequently Asked Questions

### General Questions

**What is PeerGenius.ai?**
PeerGenius.ai is an expert pre-submission manuscript review service that provides comprehensive feedback on journal papers, dissertations, theses, conference papers, and more using 7 specialist reviewers. We analyze methodology, statistics, clarity, and more, delivering detailed feedback in minutes.

**How does PeerGenius review work?**
Upload your manuscript, select a review tier, and our specialist reviewers analyze your paper in parallel. Each reviewer specializes in different aspects and provides detailed feedback with specific suggestions. Premier tier includes an Editor-in-Chief who consolidates all feedback into a decision letter.

**How long does a review take?**
- Individual reviewers: 3-5 minutes per reviewer
- Standard tier: 5-10 minutes
- Premier tier: 10-15 minutes

**How is this different from traditional peer review?**
Traditional peer review takes weeks/months and may have reviewer bias. PeerGenius provides comprehensive, multi-perspective feedback with actionable suggestions, delivered in minutes. We complement rather than replace journal peer review.

### Pricing Questions

**Can I get a refund?**
We offer refunds for technical issues that prevent review completion. Contact support@peergenius.ai within 7 days if our system fails to generate a review.

**Is there a subscription option?**
Currently, we offer pay-per-review pricing only. Contact us for institutional volume pricing.

**How is pricing calculated?**
Prices are based on your manuscript's word count. Longer papers require more AI processing and cost proportionally more. Bundle tiers (Standard and Premier) offer 25-35% savings compared to purchasing individual reviewers.

### Technical Questions

**Do you check statistics and methodology?**
Yes, our Statistical Methods Expert performs rigorous analysis including sample sizes, effect sizes, statistical test appropriateness, and provides R/Python code for corrections.

**Can I use this for journal submissions?**
Absolutely! Many researchers use PeerGenius.ai to identify and fix issues before submission. Our reviews help reduce desk rejections and improve manuscript quality.

**Do you support supplementary materials?**
Yes, upload figures, tables, and supplementary files alongside your manuscript for comprehensive review.

**How accurate is PeerGenius review?**
Our reviewers use advanced models with extended reasoning. They provide high-quality feedback comparable to expert human reviewers for many aspects, but should be used as one input among many. In validation against BMJ peer reviews, PeerGenius achieved an 8.86/10 quality score.

**Do you support non-English manuscripts?**
Our primary support is for English-language manuscripts. While we can process other languages, review quality is optimized for English.

### Privacy Questions

**Is my manuscript data secure?**
Yes. Manuscripts are encrypted, automatically deleted after 30 days, and never used for AI training.

**Who can see my manuscript?**
Only you. We don't share manuscripts with third parties or allow staff access without explicit permission.

**Can I delete my data earlier?**
Contact support@peergenius.ai to request immediate deletion of your manuscripts and reviews.

---

## Validation Evidence

### Overview
PeerGenius.ai has been compared against BMJ journal peer reviews in a preliminary analysis of 5 manuscripts published in The BMJ (2021-2023). All BMJ peer reviews are open-access under CC-BY licenses.

**Aggregate Results:**
- AI average quality score: 8.86/10 vs Journal average: 7.86/10
- Near-parity (gap < 1.0 points) achieved in 4 of 5 cases (80%)
- AI detected 8 critical methodological flaws missed by journal reviewers
- Journal detected 1 critical flaw missed by AI
- Average complementarity: 64.2% (reviews are synergistic, not redundant)

### Study-by-Study Summary

**1. Hippisley-Cox et al. (2022), QCovid4 Risk Prediction Model**
- Journal: 8.3/10, AI: 9.2/10 (gap: 0.9, near-parity)
- Complementarity: 71.7%
- AI caught: multiple testing correction needed, numerical discrepancies
- Journal excelled: clinical context for COVID-19 risk prediction, calibration insight

**2. Mok et al. (2023), Antipsychotics in Dementia**
- Journal: 7.6/10, AI: 9.6/10 (gap: 2.0, AI superior)
- Complementarity: 69.6%
- AI caught: 4 critical flaws: time-varying confounding, fracture phenotype heterogeneity, pathological fractures confounding, combination product confounding
- Journal excelled: patient-centered perspective, practical prescribing recommendations

**3. Morales et al. (2022), QOF Interrupted Time Series**
- Journal: 7.8/10, AI: 8.1/10 (gap: 0.3, near-parity)
- Complementarity: 59.1%
- AI caught: autocorrelation omission, underdetermined design
- Journal caught: graphing error (predicted = actual values)
- Ideal hybrid case: each found a critical flaw the other missed

**4. Rees et al. (2021), Shoulder Surgery Cohort**
- Journal: 7.8/10, AI: 8.8/10 (gap: 1.0, near-parity)
- Complementarity: 60.8%
- AI caught: multiple testing without correction, causal overreach
- Journal excelled: heterogeneous cohort recognition, re-operation ambiguity

**5. Woolf et al. (2023), Sildenafil Mendelian Randomisation**
- Journal: 7.8/10, AI: 8.6/10 (gap: 0.8, near-parity)
- Complementarity: 60.0%
- AI caught: GWAS sample overlap bias (~2% estimate inflation)
- Journal caught: drug misuse public health concern, Christmas article context

### 10-Dimensional Scoring Framework
Reviews are compared across 10 dimensions:
1. Statistical Rigor
2. Methodological Standards
3. Clinical/Domain Context
4. Study Design Critique
5. Data Quality & Verification
6. Interpretive Depth
7. Systematic Completeness
8. Actionability & Structure
9. Tone & Constructiveness
10. Editorial Judgment

AI consistently wins: Statistical Rigor, Systematic Completeness, Actionability & Structure
Journal consistently wins: Clinical/Domain Context, Tone & Constructiveness

### Recommendation
A complementary hybrid AI + human review model is supported by the evidence. AI provides essential first-pass screening for statistical and methodological validity. Human experts focus on clinical relevance, interpretive depth, and contextual judgment.

### Sample Reviews
Browse 5 full PeerGenius review PDFs of published BMJ manuscripts at https://peergenius.ai/samples. Each review demonstrates multi-reviewer analysis, scoring, methodology critique, statistical analysis with corrective code, and actionable feedback.

### Individual Reviewer Sample Reviews
Each of the 8 specialist reviewers has 5 sample review PDFs available. These demonstrate how each specific reviewer analyzes published BMJ manuscripts. PDFs are available at `/evidence/agents/{agent-slug}-sample-{1-5}.pdf`.

### Links
- Full evidence: https://peergenius.ai/evidence
- Sample Reviews: https://peergenius.ai/samples
- Methodology: https://peergenius.ai/evidence/methodology
- Individual study comparisons: https://peergenius.ai/evidence/studies/[slug]

---

## Troubleshooting

### Common Issues

**Review is taking longer than expected**
- Large manuscripts (>50 pages) may take up to 20 minutes
- Check your internet connection
- Contact support if review exceeds 30 minutes

**PDF text not extracting correctly**
- Ensure your PDF is not scanned/image-based
- Try converting to DOCX and re-uploading
- Check that text is selectable in your PDF reader

**Missing figures or tables in review**
- Upload figures as separate image files
- Name files descriptively (e.g., "Figure_1_Results.png")
- Ensure images are high resolution (300+ DPI)

**Review seems incomplete**
- Check that entire manuscript uploaded successfully
- Verify file size is under 10MB
- Try re-uploading if sections appear missing

**Statistical code examples not appearing**
- Ensure your manuscript contains statistical content
- Statistical Methods Expert provides code only when issues are found
- Premier tier provides most comprehensive statistical analysis

### Getting Help
- Email: support@peergenius.ai
- Response time: Within 24 hours
- Include your review ID when contacting support

---

## Institutional Plans

For research institutions, universities, and organizations reviewing multiple manuscripts:

### Volume Pricing
Contact us for custom pricing based on expected review volume.

### Features for Institutions
- Dedicated account management
- Usage reporting and analytics
- Custom branding options
- Priority support
- Flexible billing arrangements

### Contact for Institutional Plans
Email: institutional@peergenius.ai
Subject: Institutional Plan Inquiry

---

## Free Tools

### Manuscript Assessment (Big Picture)
Upload your full manuscript and get an honest editorial overview. A senior editor-style assessment that identifies specific strengths and issues with exact quotes and section references.

**Features:**
- Detects academic discipline and adapts evaluation to field-specific standards
- 3-5 strengths with manuscript references
- 5-10 issues with severity, exact quotes, and section locations
- Overall readiness verdict (Ready / Needs Work / Major Issues)
- Each issue maps to a specialist reviewer for targeted upgrade
- 2 free assessments per month (account required)
- URL: https://peergenius.ai/tools/big-picture

### Reviewer 2 Generator
Paste your abstract and get the kind of peer review comments that make you question your career choices. Free, entertaining, and uncomfortably useful.

**Features:**
- 3 "Reviewer 2" style comments per abstract (humorous but insightful)
- Desk Rejection Risk Score (Low/Moderate/High) with specific risk signals
- Share results via copy, download card, X, or LinkedIn
- 5 free uses per day, no account required
- URL: https://peergenius.ai/tools/reviewer-2

### More Free Tools
Browse all free research tools at https://peergenius.ai/tools

---

## Contact Information

**Website**: https://peergenius.ai
**Support Email**: support@peergenius.ai
**Institutional Inquiries**: institutional@peergenius.ai

## Quick Links

- Homepage: https://peergenius.ai
- Pricing: https://peergenius.ai/pricing
- FAQ: https://peergenius.ai/faq
- About: https://peergenius.ai/about
- Features: https://peergenius.ai/features
- Sample Reviews: https://peergenius.ai/samples
- Evidence: https://peergenius.ai/evidence
- Methodology: https://peergenius.ai/evidence/methodology
- Privacy Policy: https://peergenius.ai/privacy
- Terms of Service: https://peergenius.ai/terms
- Free Tools: https://peergenius.ai/tools
- Manuscript Assessment: https://peergenius.ai/tools/big-picture
- Reviewer 2 Generator: https://peergenius.ai/tools/reviewer-2
- Blog: https://peergenius.ai/blog
- Compare Tools: https://peergenius.ai/compare
- Quick Reference: https://peergenius.ai/llms.txt