GitHub Project Rigorous Launches Cloud-Based AI Peer Reviewer to Enhance Scientific Manuscript Evaluation

GitHub Project: RobertJakob/Rigorous Rigorous is an AI-powered scientific manuscript analysis tool designed to enhance transparency, reduce costs, and expedite the publication process. Available online at https://www.rigorous.company/, the cloud version is free for testing purposes. Users can upload their manuscript, specify the target journal and areas of focus, and receive a detailed PDF report via email within 1-2 working days. Project Overview and Structure The repository comprises two main components: Agent1_Peer_Review This advanced peer review system uses specialized AI agents to provide comprehensive manuscript analysis. It offers: Comprehensive Manuskript Analysis: Thorough examination of each section of the manuscript. Detailed Feedback: Insightful evaluations on scientific rigor, content quality, and writing effectiveness. Actionable Recommendations: JSON output with clear, actionable suggestions. Professional PDF Reports: Automated generation of well-formatted review reports. Agent2_Outlet_Fit Currently in development, this tool aims to assess the suitability of a manuscript for specific journals or conferences. Its features include: Core Functionality: Implementation is underway. Integration with Agent1: Seamless integration with the peer review system is planned. Ongoing Testing: Continuous testing and validation to ensure reliability. How to Generate the PDF Report To generate a professional peer review report using Agent1, follow these steps: Install Required Dependencies: Ensure you have reportlab and pillow installed. Additional dependencies are listed in the requirements.txt file. bash pip install -r requirements.txt Prepare Necessary Files: executive_summary.json: Contains the executive summary and overall scores. quality_control_results.json: Includes detailed section analyses, rigor assessments, and writing quality results. logo.png: The logo to be used in the report header. Run the PDF Generator Script: Execute the script to generate the PDF report. bash python Agent1_Peer_Review/pdf_generator.py The generated report will be saved to: - Output Location: Agent1_Peer_Review/results/review_report.pdf Features of the PDF Report Cover Page: Displays the logo, manuscript title, and overall scores. Executive Summary: Provides a concise overview of the manuscript’s strengths and areas for improvement. Detailed Analysis Pages: Breaks down assessments into specific categories (S1–S10, R1–R7, W1–W7). Tables of Scores and Suggestions: Visual representations of scores and detailed recommendations. Professional Layout: Consistent formatting, color coding, and a clean, professional appearance. For more information on the PDF generator script, refer to the comments in Agent1_Peer_Review/pdf_generator.py. System Requirements Python: Version 3.7 or higher. OpenAI API Key: Necessary for accessing AI functionalities. Manuscripts: PDF format for analysis. Dependencies: Ensure all dependencies listed in each tool's requirements.txt are installed. License This project operates under the MIT License, allowing for wide usage and modification. Contributing We welcome contributions from the community. To contribute, please submit a Pull Request with your proposed changes. Detailed guidelines can be found in the project’s CONTRIBUTING.md file. By leveraging robust AI and a structured approach, Rigorous aims to revolutionize the scientific peer review process, making it more effective and accessible for researchers worldwide.