Reviewer GuidelinesJournal of Applied Robotics and Artificial Intelligence
Peer reviewers strengthen the quality and impact of robotics and AI research.
Principles of Peer Review
Provide objective feedback that improves methodology, reporting clarity, and clinical relevance.
What to Evaluate
Focus on data quality, validation design, safety considerations, and reproducibility of robotics and AI systems.
Confidentiality and Conflicts
Maintain confidentiality and decline reviews if conflicts could affect impartiality.
Join the Reviewer Network
Register as a reviewer and support high quality publications.
Email the Editorial OfficeView Reviewer BenefitsEmail: [email protected]
JRAI Commitment
We prioritize clear decision making, ethical oversight, and consistent editorial standards for the robotics and AI community.
Review Structure
Start with a brief summary of the manuscript and overall assessment. Then provide major issues first, followed by minor corrections.
Methodology Checks
Assess study design, data sources, and validation setup to ensure claims are supported. Look for leakage, overfitting, or missing controls.
Statistical Integrity
Confirm that statistical tests are appropriate and reported with effect sizes and confidence intervals where possible. Flag unclear sample size justifications.
Reproducibility
Check whether methods and parameters are detailed enough for replication. Encourage sharing of code, data, or detailed protocols when feasible.
AI Bias
Evaluate potential bias and generalizability across patient subgroups or imaging settings. Ask for subgroup analyses when claims imply broad applicability.
Clinical Safety
Review safety considerations, failure modes, and risk mitigation for robotic systems. Ensure clinical claims align with evidence and validation.
Reporting Standards
Recommend adherence to applicable reporting guidelines and encourage structured abstracts, clear figures, and transparent limitations.
Constructive Tone
Provide respectful, actionable feedback and avoid personal criticism. The goal is to improve the work and guide authors toward clarity.
Recommendation Levels
Use clear recommendations and justify them with evidence from the manuscript. Distinguish between mandatory changes and suggestions.
Data Availability
Verify that data availability and code statements are present and accurate. Note restrictions that may affect reproducibility.
Ethical Concerns
Flag missing consent, ethics approval, or privacy safeguards. Alert the editor when ethical issues require escalation.
Figure Clarity
Check that figures and tables are readable, labeled, and supported by the text. Recommend improvements when visualization obscures results.
Reference Quality
Ensure key prior work is cited and claims are placed in context. Missing foundational references should be flagged for revision.
Limitations Emphasis
Encourage authors to state limitations clearly, including data constraints or deployment challenges. Honest limitations improve reader trust.
Supplementary Review
Review supplementary materials for critical methods or data that support conclusions, and request clarifications when needed.
Timeliness
Accept reviews only when you can meet the deadline. Prompt responses keep decisions on schedule.
