EdgeRef Peer Review

EdgeRef Peer Review is an AI-assisted pre-submission review tool for academic manuscripts.

It helps researchers check manuscript readiness, source data status, target journal fit, and journal catalog match before formal journal submission. The system generates a structured pre-submission review report with major concerns, methodological risks, source data issues, reporting gaps, and revision priorities.

EdgeRef does not replace formal journal peer review. It is designed as a pre-submission self-check and revision support tool.

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Live Demo

Coming soon.

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What EdgeRef can do

• Upload and parse academic manuscripts in PDF, DOCX, or TXT format

• Upload and summarize source data in CSV, XLSX, or ZIP format

• Run a preflight check before AI review

• Detect manuscript language and generate review comments in the same language

• Assess target journal fit based on user-provided journal information

• Match target journals against local journal catalogs, including:

  • SCIE
  • SSCI
  • AHCI
  • CSSCI
  • PKU Core
  • CSCD
  • AMI
  • Chinese Science and Technology Core
  • EI

• Generate an AI-assisted peer review-style report

• Export the report as Markdown or Word

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Review report structure

EdgeRef generates a structured report covering:

1. Editorial Summary
2. Target Journal Fit Assessment
3. Overall Recommendation
4. Major Concerns
5. Minor Concerns
6. Methodological and Statistical Review
7. Source Data and Reproducibility Review
8. Reporting and Ethics Check
9. Revision Checklist
10. Final Pre-submission Advice

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Typical use cases

EdgeRef is designed for:

• Researchers preparing a manuscript before submission
• Graduate students checking paper structure and reporting quality
• Research teams reviewing source data completeness
• Authors comparing manuscript fit with a target journal
• Institutions exploring AI-assisted research quality control

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Important limitations

EdgeRef is a pre-submission support tool. It cannot guarantee publication outcomes.

The system does not:

• replace journal editors or human peer reviewers
• certify research integrity
• verify image manipulation or forensic evidence
• guarantee acceptance by any journal
• replace official journal instructions or institutional requirements

Users should always verify journal catalog information, submission requirements, and publication policies with official sources.

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Local setup

Install dependencies:

python -m pip install -r requirements.txt

Run the app:

streamlit run app.py

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Secrets and deployment

This project uses Streamlit secrets for protected configuration.

A template is provided at:

.streamlit/secrets.example.toml

Do not commit your real secrets file:

.streamlit/secrets.toml

The .gitignore file should include:

.streamlit/secrets.toml
.env
__pycache__/
*.pyc

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Journal catalog data

The local journal catalog is stored in:

data/journal_catalogs/journal_catalog_master.csv

The catalog is used for local journal matching only. Journal directories may change over time, so final verification should always follow the latest official directory or institutional research office requirements.

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Technology stack

• Python
• Streamlit
• pandas
• openpyxl
• python-docx
• pypdf

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Disclaimer

EdgeRef Peer Review provides AI-assisted pre-submission review suggestions. The generated report is for research preparation and manuscript revision support only. It should not be treated as formal editorial advice, journal decision-making, or official peer review.

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Generated by EdgeRef.