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ASAI Evaluation Criteria

For Applied Research Manuscripts — how our double-blind peer review works and what reviewers assess.

The Process

Double-Blind Review

1
Editorial screening

Checks scope, applied value, anonymization, and that raw data files are attached.

2
Reviewer assignment

Specialists in the relevant field are invited. Authors and reviewers stay anonymous to each other.

3
Evaluation

Reviewers score each criterion and write comments for the authors and the editor.

4
Recommendation

Each reviewer recommends accept, revise, or decline; the editor makes the final decision.

Criteria

What Reviewers Assess

Our reviewers assess submissions based on these key criteria.

Priority: High

1. Industrial & Practical Relevance

  • Does the research address a specific, real-world problem in the industrial, medical, or agricultural sectors?
  • Is the proposed solution feasible and scalable in a real-world environment?
  • Reviewer Question: If a company adopted this research today, would it provide a measurable improvement?
Non-Negotiable

2. Data Integrity & Originality

  • Has the author provided the raw data/source code as required by ASAI policy?
  • Are the results consistent with the provided data?
  • Is there any suspicion of data manipulation or AI-generated results (not to be confused with AI-assisted writing)?
Standard

3. Technological Advancement & AI Integration

  • Does the research utilize modern technologies (AI, IoT, Robotics, etc.) effectively?
  • Does it contribute to the digital transformation of the specific field?
Standard

4. Environmental Impact & Sustainability

  • Does the research align with ASAI's mission of environmental preservation?
  • Does the solution contribute to waste reduction, resource efficiency, or a "healthy world" ecosystem?
Standard

5. Methodology & Technical Rigor

  • Is the experimental design sound and reproducible?
  • Are the conclusions supported by the data presented?
  • Is the literature review focused on current state-of-the-art applications?
CriterionScore (1-5)Reviewer's Comments
Practical Applicability○○○○○Completed by reviewer
Technical Innovation○○○○○Completed by reviewer
Data Transparency○○○○○Completed by reviewer
Sustainability Value○○○○○Completed by reviewer

Recommendation Options:

Accept Submission (High Impact)
Revisions Required (Minor/Major)
Decline Submission (Too Theoretical / No Applied Value)
Reviewer Ethics

Responsibilities of Reviewers

Confidentiality

Manuscripts and data under review are confidential and must not be shared or used for any other purpose.

Conflicts of Interest

Reviewers must decline any manuscript where they have a competing interest or can identify the authors.

Constructive Feedback

Comments should be specific, respectful, and help authors improve the practical value of their work.

AI in Reviewing

Reviewers must not upload confidential manuscripts or data into public AI tools.

Become an ASAI reviewer

Specialists in industry, medicine, agriculture, and AI are welcome to join our reviewer pool.

Become a Reviewer