Combating unethical publications with plagiarism detection services

Area of Science:

• Biomedical Publishing
• Scientific Integrity
• Information Science

Background:

• Approximately 3,000 new citations highly similar to previously published manuscripts appear annually in biomedical literature (MEDLINE).
• This highlights the critical need for editors and reviewers to have access to detection systems for identifying similar text in submitted manuscripts.
• Ensuring manuscript novelty is paramount in scientific publishing.

Purpose of the Study:

• To review the capabilities and considerations of software-based text similarity detection services for the biomedical publication industry.
• To inform publishers, editors, and reviewers about available tools for manuscript novelty assessment.
• To provide guidance on selecting and utilizing these services effectively.

Main Methods:

• Evaluation of commercially available and free software-based text similarity detection services.
• Comparison of services based on literature database completeness and operability.
• Analysis of specific services like CrossRef (fee-based) and etblast.org (free) tailored for biomedical publications.

Main Results:

• The capabilities of text similarity detection services vary significantly, primarily due to differences in the completeness of their literature databases.
• Most commercial software is designed for academic plagiarism detection, but some services target the biomedical sector.
• Both fee-based (CrossRef) and free (etblast.org) services are available for biomedical applications.

Conclusions:

• Software tools can intercept suspect manuscripts and act as a deterrent to plagiarism.
• Careful consideration of service capabilities, database completeness, and operational aspects is essential before selection and use.
• Effective utilization of these tools supports the integrity and novelty of biomedical publications.