Publication Ethics

The Babylonian Journal of Machine Learning (BJML) is committed to ensuring high standards of ethical conduct in academic publishing. We strongly discourage unethical practices such as plagiarism, data fabrication, falsification, and duplicate submissions without proper acknowledgment.

AI-Powered Plagiarism Detection

To uphold the integrity of scholarly work, BJML employs advanced plagiarism detection tools, including AI-powered systems like Turnitin. As of May 1, 2023, all submitted manuscripts are subjected to a rigorous similarity check prior to editorial review.

Policy on Overlapping Content

If significant similarity or overlapping text is detected, an investigation will be initiated. Manuscripts found to include substantial plagiarism or AI-generated content without proper citation will be rejected.

Upholding Research Integrity

Through these measures, BJML aims to safeguard the originality and credibility of published research. Authors are encouraged to adhere to ethical guidelines, ensuring their contributions advance knowledge responsibly and ethically.