Conflict Of Interest Checker

Check for co-authorship conflicts between authors and suggested reviewers

Reviewer conflict detection tool.

Use Cases

• Journal submission prep
• Editorial decisions
• Peer review integrity
• Compliance verification

Parameters

Parameter	Type	Default	Required	Description
--authors, -a	string	-	Yes	Comma-separated author names
--reviewers, -r	string	-	Yes	Comma-separated reviewer names
--publications, -p	string	-	No	CSV file with publication records

CSV Format

csv

author,reviewer,paper_id
Smith,Brown,paper1
Smith,Jones,paper2

Usage

bash

# Check with demo data
python scripts/main.py --authors "Smith,Jones,Lee" --reviewers "Brown,Davis,Wilson"

# Check with publication records
python scripts/main.py --authors "Smith,Jones" --reviewers "Brown,Davis" --publications pubs.csv

Returns

• Conflict flagging (coauthorship, institutional)
• Shared publication list
• Recommendation: Accept/Recuse
• Alternative reviewer suggestions

Example Output

text

⚠ Found 2 potential conflict(s):

1. COAUTHORSHIP CONFLICT
   Reviewer: Brown
   Author: Smith
   Shared papers: paper1

2. COAUTHORSHIP CONFLICT
   Reviewer: Wilson
   Author: Smith
   Shared papers: paper2

Risk Assessment

Risk Indicator	Assessment	Level
Code Execution	Python/R scripts executed locally	Medium
Network Access	No external API calls	Low
File System Access	Read input files, write output files	Medium
Instruction Tampering	Standard prompt guidelines	Low
Data Exposure	Output files saved to workspace	Low

Security Checklist

• No hardcoded credentials or API keys
• No unauthorized file system access (../)
• Output does not expose sensitive information
• Prompt injection protections in place
• Input file paths validated (no ../ traversal)
• Output directory restricted to workspace
• Script execution in sandboxed environment
• Error messages sanitized (no stack traces exposed)
• Dependencies audited

Prerequisites

No additional Python packages required.

Evaluation Criteria

Success Metrics

• Successfully executes main functionality
• Output meets quality standards
• Handles edge cases gracefully
• Performance is acceptable

Test Cases

1. Basic Functionality: Standard input → Expected output
2. Edge Case: Invalid input → Graceful error handling
3. Performance: Large dataset → Acceptable processing time

Lifecycle Status

• Current Stage: Draft
• Next Review Date: 2026-03-06
• Known Issues: None
• Planned Improvements:
  • Performance optimization
  • Additional feature support