Correction and Retracation

Correction:

If a factual error or inaccuracy is discovered in an article published in the Journal of Artificial Intelligence (JAI), authors may request a correction. Corrections must be accompanied by a clear rationale and documentation supporting the proposed changes. The correction process will involve collaboration between the authors and the editor, with the goal of correcting and correcting the erroneous information without altering the substance or main results of the research. Corrections will be published as part of the relevant journal version and will include a clear notification of the changes.

Retraction:

Retraction of an article may be considered in certain situations, such as:

Ethical Violations:

If the article involves a violation of research ethics, such as plagiarism or significant data manipulation.

Serious Methodological Errors:

If there are methodological errors that are so serious that they impact the main results of the research.

Proven Invalid or Falsified Data:

If the data presented in the article is proven to be invalid or falsified.

Falsification of Identity or Misrepresentation of Authors:

If there is falsification of the author's identity or misrepresentation involving a significant role of the author.

Joint Author and Editor Decision:

The decision to retract will be made jointly by the author and editor, taking into account the facts and clear rationale.

Retraction Notification:

If an article is retracted, a formal notice will be posted on the journal website, and the electronic version of the article will be marked "Withdrawn" with the stated reason.

Goals of the Corrections and Retractions Policy:

Maintain the integrity of the scientific literature and reader trust.
Respond to and correct factual errors with transparency.
Respond to ethical violations or other serious issues with appropriate action.

This Corrections and Retractions Policy ensures that the Journal of Artificial Intelligence (JAI) adheres to high ethical and quality standards in scientific publication, while providing clarity and transparency in managing errors or serious issues that may arise.