Peer Review Process

Peer Review Process
Applied AI & Data Science for Health, Agriculture & Environment (AIDSAE), published by EcoScribe Publishers Company Limited, operates a quality-focused peer review process designed to be fair, timely, and transparent while protecting research integrity.

1) Review Model
Double-blind peer review: authors and reviewers remain anonymous to each other. Editors may access author identities for legitimate editorial administration (e.g., scope checks, ethics verification, and conflict-of-interest screening). Authors must upload an anonymised manuscript for review and avoid self-identifying statements in the main file.

2) Editorial Screening (Pre-Review)
Every submission undergoes checks for: scope fit (health/agri/environment AI/data science), completeness (required files/statements), reporting quality, similarity/citation practices, and integrity signals (ethics/privacy, dataset permissions, conflicts, disclosures).
AIDSAE may desk reject manuscripts that are out of scope, inadequately evaluated, poorly reported, or raise integrity concerns.

3) Technical Minimums
To proceed to external review, submissions must clearly report: dataset source, validation logic (split/CV), baseline comparator(s), evaluation metrics, leakage/overfitting safeguards, error analysis/failure modes, and a reproducibility statement.

4) External Peer Review
AIDSAE typically invites two independent reviewers for full research articles. For short reports or narrow technical notes, the editor may use one external review plus an editorial technical check.

6) Editorial Decisions
Accept / Minor revision / Major revision / Reject

7) Appeals & Complaints
Authors may appeal with a clear scientific rationale. Complaints about process or ethics can be submitted to the editorial office.