1. Introduction Peer review is the cornerstone of the scientific publication process. Engineering Artificial Intelligence relies on the expertise and dedication of our reviewers to ensure the quality, validity, and relevance of the research we publish. We sincerely appreciate the time and effort you dedicate to evaluating manuscripts.

 

2. Ethical Responsibilities

· Confidentiality: The manuscript is a privileged document. It must not be shown to or discussed with others except as authorized by the Editor. Do not retain copies of the manuscript or use the data/ideas contained therein for your own research before publication.

· Conflict of Interest: If you suspect a conflict of interest (e.g., you recognize the authors despite anonymization, work in the same institution, or are in direct competition), please decline the invitation or notify the Editor immediately.

· Timeliness: Please respond to the review invitation promptly. If you accept, adhere to the deadline. If you require an extension, inform the Editorial Office as soon as possible.

 

3. The Single Anonymized Review Policy Engineering Artificial Intelligence operates a single anonymized review process:

· Author Identification: Reviewers may have access to the authors’ identities and affiliations as part of the submission. If you believe the manuscript contains inappropriate content that could compromise editorial integrity (e.g., attempts to influence reviewers, undisclosed conflicts, or suspicious statements), please notify the Editor.

· Anonymity of Reviewers: Do not sign your name within your review comments. Your identity will remain confidential to the authors.

 

4. Evaluation Criteria Please assess the manuscript based on the following key aspects:

· Originality & Novelty: Does the paper present new ideas, methods, or significant improvements over existing techniques? Is the contribution distinct enough from previous literature?

· Scope & Relevance: Does the topic fall within the scope of Engineering Artificial Intelligence? Does it demonstrate a meaningful convergence of AI theories with engineering applications?

· Technical Soundness (Methodology):

o Are the AI/Machine Learning models correctly chosen and implemented?

o Is the engineering context (physical constraints, system dynamics) respected?

o Are the mathematical derivations and experimental designs correct?

o For AI papers: Check if the training data is described sufficiently and if the hyperparameters are transparent.

· Reproducibility: Are the methods described in sufficient detail for another researcher to reproduce the results? Is the code/data availability statement present?

· Clarity & Presentation: Is the abstract an accurate summary? Is the English clear and grammatically correct? Are figures and tables legible and necessary?

 

5. Structure of Your Review Report Your review should be submitted via the online system and typically consists of two parts:

A. Confidential Comments to the Editor

· Your recommendation (Accept, Revise, Reject).

· Any confidential concerns regarding plagiarism, dual submission, or ethical issues.

B. Comments to the Authors (Constructive Feedback)

· Summary: Start with a brief summary of the paper’s contribution as you understand it.

· General Assessment: State your overall impression of the paper's strengths and weaknesses.

· Major Comments: List significant flaws that must be addressed (e.g., errors in methodology, missing controls, lack of novelty, insufficient analysis).

· Minor Comments: List smaller issues (e.g., ambiguous sentences, labeling errors in figures, typos, formatting deviations).

Note: Please be constructive and professional. Avoid hostile or derogatory language. The goal is to help the authors improve their work, even if the recommendation is rejection.

 

6. Recommendations Based on your assessment, please select one of the following recommendations:

· Accept: The manuscript is scientifically sound and requires no further changes.

· Minor Revision: The manuscript requires small changes (clarification, textual edits, minor analysis additions) before acceptance.

· Major Revision: The manuscript has potential but requires significant reworking (new experiments, major rewriting, fixing serious technical flaws).

· Reject: The manuscript is flawed, lacks originality, is outside the scope, or makes no significant contribution.

 

7. AI-Generated Content Check While authors are permitted to use AI tools for language polishing, the core scientific contribution must be human-driven.

· If you suspect that parts of the text are nonsensical or "hallucinated" by AI, or if the references seem fabricated, please flag this to the Editor.