Retraction Policy

The International Journal of AI and Machine Learning (IJAIML) is firmly committed to preserving the integrity, accuracy, transparency, and long-term reliability of the scholarly record. The journal recognizes that trust in published research is a cornerstone of scientific progress and is essential for advancing science, technology, and innovation, particularly in fast-developing and high-impact fields such as artificial intelligence and machine learning. Ensuring the credibility of published work is fundamental not only to the reputation of the journal, but also to the responsible growth of the global research ecosystem.

IJAIML acknowledges that, despite rigorous peer review and editorial oversight, situations may arise in which published articles are later found to contain serious errors, ethical concerns, or factual inaccuracies. In such cases, it is the responsibility of the journal to take appropriate corrective action to safeguard the scholarly literature and to inform readers clearly and transparently about the reliability of affected research findings.

Retraction is regarded as an essential mechanism for correcting the academic literature when serious issues are identified that undermine the validity, originality, or ethical integrity of a published article. These issues may include, but are not limited to, plagiarism, data fabrication or falsification, duplicate publication, significant methodological errors, unethical research practices, or legal and copyright violations. Retraction serves to prevent the continued citation and use of unreliable research and to maintain confidence in the academic record.

The International Journal of AI and Machine Learning follows internationally accepted principles of publication ethics and best practices in the management of retractions. All retraction decisions are handled in a responsible, fair, objective, and transparent manner, with careful consideration of the evidence and the perspectives of all parties involved. The journal emphasizes that retraction is not intended as a punitive measure against authors, but rather as a necessary step to correct the literature and uphold the standards of scholarly communication.

IJAIML is committed to ensuring that the retraction process is conducted with due respect for confidentiality, due process, and academic fairness. Authors are informed of concerns and provided with an opportunity to respond or clarify before a final decision is made. Retraction notices are issued promptly when required and are clearly linked to the original articles to ensure transparency for readers and indexing services.

By maintaining a clear and robust retraction policy, the International Journal of AI and Machine Learning demonstrates its dedication to ethical publishing, academic accountability, and research integrity. Through transparent correction of the scholarly record, the journal seeks to protect the interests of the research community, support responsible scientific advancement, and reinforce public trust in artificial intelligence and machine learning research.