Reviewer Guidelines
JPUB AI follows a single-blind peer-review process. Reviewers remain anonymous to authors, while reviewers are aware of the authors' identities.
Reviewers play an important role in maintaining the scientific quality, technical rigor, ethical standards, and integrity of the journal.
Reviewer Qualifications and Expertise
Reviewers should accept assignments only when they have appropriate expertise, methodological knowledge, or professional experience relevant to the manuscript.
Relevant expertise may include:
- Artificial Intelligence
- Machine Learning
- Deep Learning
- Data Science
- Computer Science
- Robotics
- Intelligent Systems
- Natural Language Processing
- Computer Vision
- Data Mining
- Computational Statistics
- Human-Computer Interaction
- AI applications in science, engineering, healthcare, business, or other relevant fields
Reviewers should decline assignments when they do not have sufficient expertise to provide a reliable assessment.
Reviewer Responsibilities
Reviewers should provide independent, objective, constructive, and evidence-based assessments. Reviews should focus on the scientific and technical quality of the manuscript rather than the authors personally.
Evaluation Criteria
Reviewers should consider, where applicable:
- Relevance to the journal's aims and scope
- Originality and novelty
- Clarity of the research question
- Technical and methodological soundness
- Appropriateness of experiments or computational analysis
- Validity of results
- Quality of interpretation
- Reproducibility and transparency
- Ethical and responsible research practices
- Overall contribution to the field
AI and Machine Learning Research
For AI and machine-learning manuscripts, reviewers should consider whether the methodology is sufficiently described and whether the evaluation is appropriate for the stated research question.
Where applicable, reviewers should examine dataset selection, preprocessing, training procedures, validation methods, baseline comparisons, evaluation metrics, hyperparameters, statistical analysis, robustness, and limitations.
Data and Computational Reproducibility
Reviewers should assess whether the manuscript provides sufficient information about datasets, algorithms, software, computational procedures, and analytical methods to allow meaningful evaluation or reproduction of the research where appropriate.
Reviewers should not require disclosure of confidential, proprietary, personally identifiable, or legally restricted information where disclosure would be inappropriate.
Responsible and Ethical AI
Where relevant, reviewers should consider issues including bias, fairness, privacy, security, transparency, explainability, safety, misuse, and societal impact.
Reviewers should distinguish genuine methodological or ethical concerns from differences in reasonable scientific or technical choices.
Human Participants and Personal Data
For studies involving human participants, user studies, personal data, or potentially identifiable information, reviewers should consider whether appropriate ethical approval, consent, privacy protection, and data-handling procedures are adequately described where applicable.
Robotics and Experimental Systems
For robotics and intelligent-system research, reviewers should consider whether experimental conditions, system specifications, evaluation procedures, safety considerations, and limitations are sufficiently described.
Conflict of Interest
Reviewers must disclose any actual, potential, or perceived conflict of interest before accepting or completing a review.
Conflicts may include financial relationships, institutional relationships, close personal relationships, recent collaboration, supervisory relationships, competitive interests, or other circumstances that could affect impartiality.
Confidentiality
Manuscripts must be treated as confidential documents. Reviewers must not share, copy, distribute, discuss, or use unpublished manuscript information for personal, professional, academic, or commercial purposes.
Reviewer Comments
Comments should be professional, specific, constructive, evidence-based, and focused on improving the manuscript.
Reviewers should distinguish major issues that materially affect the validity or publication suitability of the work from minor issues involving clarity, presentation, terminology, or references.
Use of Artificial Intelligence in Peer Review
Reviewers must not upload confidential manuscripts or unpublished manuscript content to publicly accessible generative AI systems or other external tools unless expressly authorized and appropriate confidentiality safeguards are in place.
AI-assisted tools must not replace the reviewer's independent scholarly judgment.
Plagiarism and Research Misconduct
Reviewers should confidentially alert the editor if they identify or suspect plagiarism, substantial text reuse, duplicate publication, fabricated or falsified data, inappropriate image manipulation, undisclosed conflicts of interest, manipulated peer review, or other research misconduct.
Reviewers should not independently contact authors to investigate suspected misconduct.
Reviewer Recommendation
Reviewers may recommend acceptance, minor revision, major revision, or rejection. Reviewer recommendations are advisory and do not constitute the final publication decision.
Editorial Decision
The Editor-in-Chief has overall responsibility for the journal's editorial decisions and publication integrity. The Editor-in-Chief may delegate manuscript handling and decision-making to a qualified Senior Editor, Associate Editor, or other formally designated editor.
Reviewers provide expert advice to the editor and do not make publication decisions on behalf of the journal.