Reviewer Guidelines

Reviewer Guidelines

The Journal of Machine Learning Innovations and Artificial Intelligence Horizons (JMLIAIH) relies on the expertise and dedication of reviewers to ensure the quality, originality, and integrity of the research it publishes. Reviewers play a critical role in maintaining the high standards of the journal and providing constructive feedback to authors.

 

Responsibilities of Reviewers

  1. Evaluate the Manuscript’s Quality:
    • Assess the originality, relevance, and significance of the manuscript to the fields of machine learning and artificial intelligence.
    • Examine the clarity, coherence, and organization of the manuscript.
  2. Provide Constructive Feedback:
    • Offer specific and actionable suggestions to improve the manuscript.
    • Avoid overly critical or vague comments; focus on constructive critique.
  3. Ensure Objectivity:
    • Maintain an impartial attitude and evaluate the manuscript solely on its academic merit, without personal bias or discrimination.
  4. Respect Confidentiality:
    • Treat the manuscript and its content as confidential.
    • Do not share or discuss the manuscript with unauthorized parties.
  5. Identify Ethical Concerns:
    • Alert the editors to any suspected ethical issues, including plagiarism, data fabrication, or conflicts of interest.
  6. Meet Deadlines:
    • Complete the review within the agreed timeframe. If additional time is needed, inform the editorial office promptly.
  7. Disclose Conflicts of Interest:
    • Inform the editor of any conflicts of interest (e.g., personal, financial, or academic) that might compromise your objectivity.

 

Review Process

  1. Acceptance of Review Invitation:
    • Upon receiving an invitation, confirm your availability and expertise to review the manuscript.
    • If you feel unqualified or unable to complete the review within the deadline, notify the editor immediately.
  2. Initial Assessment:
    • Read the manuscript to determine its relevance and overall quality.
    • Ensure the manuscript fits within the journal’s scope and adheres to submission guidelines.
  3. Detailed Evaluation:
    Provide feedback on the following:
    • Originality: Does the manuscript present novel and valuable insights?
    • Technical Soundness: Are the methodologies and analyses rigorous and accurate?
    • Relevance: Does the manuscript align with current advancements in machine learning and AI?
    • Clarity: Is the writing clear, concise, and well-organized?
    • References: Are citations comprehensive, accurate, and appropriate?
  4. Recommendation:
    • Recommend one of the following decisions:
      • Accept without revision.
      • Minor revisions required.
      • Major revisions required.
      • Reject.
    • Justify your recommendation with clear, specific comments.

 

Providing Feedback

  • Positive Comments: Acknowledge the strengths of the manuscript.
  • Critical Comments: Highlight weaknesses and suggest ways to address them.
  • Formatting Suggestions: Point out inconsistencies in formatting, figures, or tables if necessary.

 

Ethical Considerations

  • Avoid Bias: Focus on the content, not the identity or affiliation of the authors.
  • Confidentiality: Do not use information from the manuscript for personal research or share it with others.
  • Report Concerns: Notify the editor of any ethical issues or potential misconduct.