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ijmdm maintains an Editorial Board of practicing researchers from around the world, to ensure manuscripts are handled by editors who are experts in the field of study.
Mr. Dr S J Vijay
Associate Professor
Editor
International Journal of Machine Design and Manufacturing
Email :
Publisher
STM Journals, An imprint of Consortium e-Learning Network Pvt. Ltd.
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AI Usage for Authors
Last Updated on: 01 Jan 2025
Introduction
Purpose
The International Journal of Machine Design and Manufacturing recognizes the increasing role of Artificial Intelligence (AI) in scientific research, writing, and publishing. While AI can enhance research efficiency, its improper use may lead to ethical concerns, misinformation, and integrity issues in scholarly publishing. This policy aims to establish clear guidelines on the acceptable use of AI in manuscript preparation, data analysis, and research writing. This ensures transparency, accountability, and compliance with academic integrity standards.
Scope and Applicability
The policy applies to all authors submitting manuscripts to the International Journal of Machine Design and Manufacturing, including research articles, reviews, short communications, and other scholarly contributions. It governs the use of AI-assisted tools in:
- Writing and editing manuscripts
- Data analysis and computational modeling
- Image and figure generation
- Literature review and citation management
The policy aligns with ethical publishing standards set by COPE (Committee on Publication Ethics) and industry best practices. It applies to all AI tools, including but not limited to text generators (e.g., ChatGPT), image generators, AI-assisted data analysis tools, and automated literature review platforms.
Definition of AI in Research
For this policy, Artificial Intelligence (AI) refers to software and algorithms capable of performing tasks that typically require human intelligence. These include, but are not limited to:
- Generative AI (e.g., ChatGPT, Bard, Claude) for text generation and paraphrasing
- Machine Learning Algorithms for data processing and pattern recognition
- AI-Based Image Processing for figure generation and enhancement
- Automated Citation and Reference Managers using AI-assisted tools
- AI-Powered Data Analysis Tools for computational modeling
While AI can be a useful aid in research, its use must be transparent, and ethical, and should not compromise the originality, credibility, or integrity of scientific publications.
Acceptable Use of AI in Research
AI tools can be valuable assets in research and manuscript preparation when used responsibly. Authors may use AI to enhance efficiency and accuracy but must ensure that all AI-assisted contributions are disclosed, verifiable, and do not compromise research integrity. Below are the acceptable uses of AI in different aspects of scholarly publishing.
- AI-Assisted Research and Writing
Authors may use AI-based tools to assist in certain aspects of manuscript writing and editing, provided that:- AI-generated text is not used as a direct replacement for the author’s intellectual contributions.
- AI tools are limited to grammar checking, language enhancement, and readability improvements.
- AI-generated content is fact-checked for accuracy, as AI models may produce incorrect or biased information.
- The use of AI tools for writing must be disclosed in the manuscript’s Acknowledgments or Methods section.
Example of AI-Assisted Writing:
✔ Acceptable: Using AI for grammar correction, sentence restructuring, and language refinement.
✖ Unacceptable: Relying on AI to generate large portions of the manuscript without substantial human oversight.
- AI for Data Analysis and Computation
AI and machine learning (ML) tools are increasingly used for computational modeling, simulation, and data interpretation in ijmdm research. AI-assisted data analysis is acceptable under the following conditions:
- The methodology, including AI tools and algorithms used, must be explicitly stated in the Methods section.
- The AI-generated outputs must be validated against experimental or established theoretical models.
- The reproducibility and reliability of AI-assisted analyses must be ensured, and datasets should be available for verification (where applicable).
- Any AI-assisted prediction models must be accompanied by appropriate statistical validation and error analysis.
- AI in Image and Figure Generation
AI-based tools may be used to generate, enhance, or process images, graphs, and diagrams in research papers, provided that:
- The source of AI-generated figures is disclosed in the Figure Legend or Methods section.
- AI-generated images are not manipulated in a way that misrepresents research findings.
- Authors ensure that AI tools do not introduce artifacts or distortions that compromise scientific accuracy.
- Ethical considerations, such as avoiding AI-generated misleading visuals, are adhered to.
Example of AI-Assisted Image Generation:
✔ Acceptable: Using AI for enhancing microscopy images, data visualization, and graphical abstracts.
✖ Unacceptable: Using AI to fabricate experimental images or misleadingly modify results.
- AI in Literature Review and Citation Management
AI tools can assist in literature searches and reference management, but authors must:
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- Verify all AI-recommended citations for accuracy and relevance.
- Ensure that AI-generated references correspond to real, peer-reviewed sources.
- Avoid AI-generated fake citations, as these constitute research misconduct.
- Clearly state the use of AI-assisted literature review tools in the Methods section.
Example of AI-Assisted Literature Review:
✔ Acceptable: Using AI to search for relevant papers and organize references in citation managers.
✖ Unacceptable: Including AI-generated references without verifying their authenticity.
Restrictions on AI Use
While AI can assist in various aspects of research and manuscript preparation, its use must be carefully regulated to maintain academic integrity. Misuse of AI tools can lead to ethical violations such as plagiarism, fabrication, and misrepresentation of research. The following restrictions must be observed when using AI in scholarly publishing.
- Prohibition on Fully AI-Generated Manuscripts
The [Journal Name] does not accept manuscripts that are entirely generated by AI.
- AI cannot be credited as an author or co-author in any submission.
- Authors must ensure that all intellectual contributions, including hypotheses, discussions, and conclusions, are made by human researchers.
- Any AI-assisted content (such as text drafting, figure generation, or data analysis) must be explicitly acknowledged.
Example:
✔ Acceptable: Using AI for grammar and language assistance while ensuring the manuscript is written by the authors.
✖ Unacceptable: Submitting a manuscript where a significant portion of the content is generated by AI without human verification.
- AI and Plagiarism Concerns
AI-generated content can lead to unintentional plagiarism, paraphrasing without proper citation, or misrepresentation of sources. To prevent this:
- The AI-assisted text should be reviewed to ensure originality and proper attribution.
- AI-generated content must not copy or closely paraphrase existing literature without citation.
- Authors must not use AI to rewrite or rephrase content from other sources to evade plagiarism detection tools.
Example:
✔ Acceptable: Using AI to summarize findings while ensuring proper citations and originality.
✖ Unacceptable: Using AI to generate content by paraphrasing existing studies without attribution.
- Misrepresentation of AI-Generated Content
Authors must not present AI-generated materials as original research findings. The following practices are strictly prohibited:
- Fabricating experimental data or results using AI.
- Using AI to generate synthetic images or graphs without clear disclosure.
- Altering AI-generated content in a way that misleads readers or distorts scientific facts.
All AI-assisted contributions must be transparently disclosed in the Methods or Acknowledgments section to uphold research credibility.
Example:
✔ Acceptable: Clearly stating that AI was used for figure enhancement in the Methods section.
✖ Unacceptable: Using AI to generate experimental images and presenting them as real laboratory results.
Disclosure and Transparency Requirements
To maintain research integrity and ensure transparency in scholarly publishing, authors must fully disclose any use of AI tools in their research and manuscript preparation. Transparency allows for proper evaluation of the work while preventing ethical concerns related to AI-generated content. The following disclosure requirements must be met by all authors submitting to the ijmdm.
- Mandatory AI Usage Disclosure
- Authors must explicitly state if AI tools were used at any stage of the research or manuscript preparation process.
- The disclosure must specify the type of AI tool used (e.g., text generation, language refinement, data analysis, figure creation).
- This disclosure should appear in the Methods or Acknowledgments section of the manuscript.
- Failure to disclose AI usage may lead to rejection or retraction of the manuscript if discovered post-publication.
Example of AI Disclosure Statement:
“Portions of this manuscript, including language enhancement and grammar checks, were assisted by [AI Tool Name], but all intellectual content, analysis, and conclusions were generated by the authors.”
- How to Cite AI-Generated Contributions
If AI-generated content plays a significant role in the research process, it must be cited appropriately:
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- AI tools should not be listed as authors.
- AI-generated text, images, or data should be referenced in footnotes, the Methods section, or an appendix.
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- AI tools can be cited following guidelines from organizations like APA or MLA, where applicable.
Example of AI Citation in References:
OpenAI. (2024). ChatGPT (version 4.0). https://openai.com/chatgpt
- AI Tools and Models to Be Mentioned in Methods Section
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- If AI was used for data analysis, figure generation, or literature review, the specific tool, model version, and parameters used must be described in the Methods section.
- The methodology should detail how AI-assisted findings were validated to ensure research credibility.
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- If AI-generated figures, graphs, or data visualizations are included, the software used must be acknowledged in the corresponding figure legends.
Example of AI Disclosure in the Methods Section:
“We used OpenAI’s ChatGPT-4 for grammatical review and summarization assistance. Data visualization was performed using AI-assisted tools, specifically [Software Name], with manual verification to ensure accuracy.”
Authorship and Accountability
Authorship carries significant academic responsibility, including the integrity, originality, and accountability of the published work. AI tools, while useful in research and writing, cannot assume authorship roles or accountability for the intellectual content of a paper. This section outlines the principles of authorship and the ethical considerations of AI use in scholarly publishing.
- AI Cannot Be Listed as an Author
- AI tools, including text-generation models (e.g., ChatGPT, Bard) and data analysis tools, cannot be credited as authors.
- Authorship in scholarly publishing requires the ability to take responsibility for the research findings, something AI cannot do.
- The ijmdm follows COPE (Committee on Publication Ethics) guidelines, which state that an author must be able to:
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- Make significant intellectual contributions to the work.
- Be accountable for the accuracy and integrity of the content.
- Provide meaningful revisions and respond to peer review.
Example of an Unacceptable Authorship Claim:
✖ “Author: OpenAI ChatGPT”
Example of Acceptable Authorship Acknowledgment:
✔ “The authors used ChatGPT-4 for language improvement and summarization but take full responsibility for the intellectual content of this paper.”
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- Author Responsibility for AI-Generated Content
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- Authors are fully responsible for the accuracy, integrity, and originality of AI-assisted content in their manuscripts.
- Any factual errors, misleading statements, or ethical concerns arising from AI-generated text, figures, or data are the sole responsibility of the authors.
- AI-generated material must be reviewed, verified, and edited by human researchers before submission.
- Misuse of AI, including submitting AI-generated content as original research or failing to disclose AI assistance, may result in manuscript rejection, retraction, or institutional notification.
Example of Author Responsibility:
✔ If an AI-assisted literature review tool recommends incorrect citations, the author must verify and correct them before submission.
✖ If AI-generated content introduces false claims, the author cannot attribute blame to the AI tool.
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- Ethical Implications of AI in Research Writing
AI use in research writing raises important ethical concerns, including:
- Risk of Fabrication: AI may generate non-existent data, references, or experiments. Authors must ensure all reported data is authentic.
- Bias and Misinformation: AI models can reflect biases present in their training data. Authors must critically assess AI-generated content for accuracy.
- Intellectual Ownership: AI cannot generate novel scientific insights independently; the research and its conclusions must come from human authors.
- Peer Review Considerations: Reviewers and editors must be aware of AI use to evaluate the manuscript appropriately.
AI and Data Integrity
Ensuring data integrity is fundamental in scientific research. AI-based tools are increasingly used for data analysis, modeling, and pattern recognition. However, improper or undisclosed use of AI can compromise the reliability and reproducibility of research findings. This section outlines the acceptable and ethical use of AI in data analysis, synthetic data generation, and verification of AI-assisted research.
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- AI in Experimental Data Analysis
AI tools can assist in data processing, statistical analysis, and interpretation, but their use must be transparent and validated:- AI-assisted data analysis must be explicitly described in the Methods section, including the software, model version, and parameters used.
- Authors must validate AI-derived results against experimental or manually derived data to ensure accuracy.
- AI should not be used to manipulate or selectively alter data in a way that misrepresents findings.
- AI-assisted statistical models must be reproducible and accompanied by appropriate validation metrics (e.g., error margins, and confidence intervals).
Example of AI Use in Data Analysis:
✔ Acceptable: Using AI for pattern recognition in ijmdm behavior, with proper validation against experimental results.
✖ Unacceptable: Using AI to filter or modify experimental data without disclosure, leading to biased conclusions.
- AI in Experimental Data Analysis
- AI-Generated Synthetic Data
AI-generated synthetic data, such as simulated material behavior, must be used cautiously and ethically:
- Authors must clearly distinguish between real experimental data and AI-generated synthetic data.
- The methodology behind synthetic data generation must be described in detail, including the AI model and training dataset.
- AI-generated data should be used to complement, not replace, real-world experimental data.
- Ethical concerns regarding bias, overfitting, or unrealistic simulations must be addressed.
Example of AI Use in Synthetic Data:
✔ Acceptable: Using AI to simulate molecular structures of ijmdm and comparing them with actual experimental results.
✖ Unacceptable: Substituting real experimental findings with AI-generated synthetic data without disclosure.
- Verifiability and Reproducibility of AI-Assisted Research
Research findings must be reproducible and verifiable, regardless of AI assistance:
- AI-assisted computations and simulations must be repeatable by independent researchers using the described methodology.
- Authors should provide access to the AI models, datasets, or algorithms used, where applicable, to ensure transparency.
- If AI was used for data analysis or prediction models, sensitivity analyses and validation studies must be included.
- AI-generated research outputs must align with the principles of open science, allowing for scrutiny and verification.
Example of Reproducible AI-Assisted Research:
✔ Acceptable: Providing the source code and AI parameters used in ijmdm to allow independent verification.
✖ Unacceptable: Using proprietary AI tools without explaining the methodology, making independent verification impossible.
Consequences of Policy Violations
Failure to adhere to the AI Use Policy may result in serious consequences, including manuscript rejection, retraction, and institutional investigations. The ijmdm is committed to maintaining the highest standards of research integrity and will take necessary action against violations related to undisclosed or unethical AI use.
- Rejection of Non-Compliant Manuscripts
Manuscripts that do not comply with the AI Use Policy may be rejected at any stage of the review process. Reasons for rejection include:
- Failure to disclose AI usage in manuscript preparation.
- Submitting AI-generated content as original research without human verification.
- Use of AI-generated synthetic data without proper validation or explanation.
- Plagiarism or AI-assisted paraphrasing without proper attribution.
If a manuscript is found to be in violation:
- Pre-submission stage: The manuscript may be rejected without review.
- During peer review: Reviewers may recommend rejection if AI use is unethical or undisclosed.
- Post-acceptance: If AI violations are detected after acceptance but before publication, the manuscript may be withdrawn.
Example of Policy Enforcement:
✔ Acceptable: Authors disclose AI usage and provide necessary validation for AI-assisted content.
✖ Unacceptable: Authors submit a manuscript generated largely by AI without disclosure, leading to rejection.
- Retraction and Corrections for Undisclosed AI Use
If an article is published and later found to contain undisclosed AI-generated content that violates journal policies, the following actions may be taken:
- Retraction: ijmdm reserves the right to retract the article if AI-generated text, images, or data were presented as original research without proper disclosure.
- Correction Notices: If AI-assisted content is found to be used improperly but does not compromise the overall validity of the research, a correction notice may be issued.
- Editorial Investigation: The editorial team may review past submissions from the same authors to ensure compliance with prior publications.
Example of Retraction Case:
✔ Acceptable: Authors request a post-publication correction to clarify AI use.
✖ Unacceptable: Authors fail to disclose AI-assisted data fabrication, leading to retraction.
- Institutional Notification and Ethical Committee Involvement
Serious violations, including AI-assisted research misconduct, may lead to formal investigations by the author’s institution or ethics committees:
- The journal may notify the corresponding author’s institution or research ethics board if AI-related misconduct is identified.
- Cases involving data fabrication, falsification, or AI-generated fraudulent content may be reported to COPE (Committee on Publication Ethics) for further action.
- Funding agencies, collaborators, and co-authors may also be informed if AI misuse significantly affects research integrity.
Example of Ethical Committee Involvement:
✔ Acceptable: Authors acknowledge an oversight and cooperate with the editorial team to correct AI-related issues.
✖ Unacceptable: Authors knowingly submit AI-generated fake research, leading to an institutional ethics investigation.
By enforcing strict consequences, ijmdm upholds ethical research practices and prevents AI misuse in scholarly publishing.
Future Amendments and Updates
The field of artificial intelligence is rapidly evolving, and its applications in research and publishing continue to expand. To ensure that ijmdm remains aligned with ethical standards, best practices, and technological advancements, this AI Use Policy will be periodically reviewed and updated as necessary.
- Periodic Review of AI Policy
- This policy will be reviewed annually or as needed to accommodate changes in AI regulations, scholarly publishing standards, and research ethics.
- Updates will be based on recommendations from:
- Committee on Publication Ethics (COPE)
- International Committee of Medical Journal Editors (ICMJE)
- STM Association and other relevant bodies.
- Authors will be notified of any significant policy updates through journal announcements, website updates, and editorial communications.
Example of Policy Review Process:
✔ Acceptable: Annual review to incorporate new AI regulations and ethical considerations.
✖ Unacceptable: Maintaining outdated AI policies that fail to address new technological developments.
- Adaptation to Evolving AI Technologies
- ijmdm that AI technologies will continue to improve and integrate into various aspects of research.
- Future updates may address:
- AI-enhanced peer review and editorial decision-making.
- AI-generated code, datasets, and simulations in research methodologies.
- New AI-driven citation and literature review tools that may impact research practices.
- ijmdm remains open to ethical AI advancements while ensuring transparency, accountability, and research integrity.