AI Integrated Manuscript Evaluation and Prioritization Workflow

AI-Assisted Manuscript Evaluation and Prioritization

1. Manuscript Submission

1.1 Author Submission

Authors submit their manuscripts through an online platform.

1.2 Initial Acknowledgment

An automated email confirmation is sent to authors upon submission.

2. AI-Powered Manuscript Screening

2.1 Plagiarism Detection

Utilize tools such as Turnitin or Grammarly to check for originality and plagiarism.

2.2 Formatting and Compliance Check

Implement AI tools like Typeset.io to ensure manuscripts meet journal formatting guidelines.

3. Content Evaluation

3.1 AI-Driven Content Analysis

Employ AI tools such as ContentBot to analyze manuscript readability, tone, and engagement level.

3.2 Topic Relevance Assessment

Use IBM Watson to assess the relevance of the manuscript against current trends and topics in the field.

4. Reviewer Assignment

4.1 AI-Based Reviewer Matching

Implement AI algorithms to match manuscripts with appropriate reviewers based on expertise and past review history, utilizing platforms like Peerage.

5. Review Process

5.1 Automated Review Reminders

Send automated reminders to reviewers using email automation tools.

5.2 AI-Enhanced Review Analysis

Use AI tools to analyze reviewer comments for sentiment and consensus, aiding in decision-making.

6. Decision Making

6.1 AI-Driven Decision Support

Utilize decision support systems that aggregate reviewer feedback and provide recommendations for acceptance, revision, or rejection.

6.2 Final Decision Communication

Communicate the final decision to authors through an automated email system.

7. Post-Evaluation Process

7.1 Feedback Collection

Gather feedback from authors and reviewers on the evaluation process using survey tools like SurveyMonkey.

7.2 Continuous Improvement

Analyze feedback data to improve the AI-assisted evaluation process, ensuring ongoing enhancement of tools and methodologies.