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Original Article
- Development of a decision-support tool to quantify authorship contributions in clinical trial publications
- Sam T. Mathew, Habeeb Ibrahim Abdul Razack, Prasanth Viswanathan
- Sci Ed. 2022;9(1):22-29. Published online February 20, 2022
- DOI: https://doi.org/10.6087/kcse.259
- 4,923 View
- 338 Download
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Abstract
PDF - Purpose: This study aimed to develop a decision-support tool to quantitatively determine authorship in clinical trial publications.
Methods
The tool was developed in three phases: consolidation of authorship recommendations from the Good Publication Practice (GPP) and International Committee of Medical Journal Editors (ICMJE) guidelines, identifying and scoring attributes using a 5-point Likert scale or a dichotomous scale, and soliciting feedback from editors and researchers.
Results
The authorship criteria stipulated by the ICMJE and GPP recommendations were categorized into 2 Modules. Criterion 1 and the related GPP recommendations formed Module 1 (sub-criteria: contribution to design, data generation, and interpretation), while Module 2 was based on criteria 2 to 4 and the related GPP recommendations (sub-criteria: contribution to manuscript preparation and approval). The two modules with relevant sub-criteria were then differentiated into attributes (n = 17 in Module 1, n = 12 in Module 2). An individual contributor can be scored for each sub-criterion by summing the related attribute values; the sum of sub-criteria scores constituted the module score (Module 1 score: 70 [contribution to conception or design of the study, 20; data acquisition, 7; data analysis, 27; interpretation of data, 16]; Module 2 score: 50 [content development, 27; content review, 18; accountability, 5]). The concept was integrated into Microsoft Excel with adequate formulae and macros. A threshold of 50% for each sub-criterion and each module, with an overall score of 65%, is predefined as qualifying for authorship.
Conclusion
This authorship decision-support tool would be helpful for clinical trial sponsors to assess and provide authorship to deserving contributors.
Review
- Artificial intelligence-assisted tools for redefining the communication landscape of the scholarly world
- Habeeb Ibrahim Abdul Razack, Sam T. Mathew, Fathinul Fikri Ahmad Saad, Saleh A. Alqahtani
- Sci Ed. 2021;8(2):134-144. Published online July 27, 2021
- DOI: https://doi.org/10.6087/kcse.244
- 18,085 View
- 625 Download
- 12 Web of Science
- 12 Crossref
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Abstract
PDF
- The flood of research output and increasing demands for peer reviewers have necessitated the intervention of artificial intelligence (AI) in scholarly publishing. Although human input is seen as essential for writing publications, the contribution of AI slowly and steadily moves ahead. AI may redefine the role of science communication experts in the future and transform the scholarly publishing industry into a technology-driven one. It can prospectively improve the quality of publishable content and identify errors in published content. In this article, we review various AI and other associated tools currently in use or development for a range of publishing obligations and functions that have brought about or can soon leverage much-demanded advances in scholarly communications. Several AI-assisted tools, with diverse scope and scale, have emerged in the scholarly market. AI algorithms develop summaries of scientific publications and convert them into plain-language texts, press statements, and news stories. Retrieval of accurate and sufficient information is prominent in evidence-based science publications. Semantic tools may empower transparent and proficient data extraction tactics. From detecting simple plagiarism errors to predicting the projected citation impact of an unpublished article, AI’s role in scholarly publishing is expected to be multidimensional. AI, natural language processing, and machine learning in scholarly publishing have arrived for writers, editors, authors, and publishers. They should leverage these technologies to enable the fast and accurate dissemination of scientific information to contribute to the betterment of humankind.
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Citations
Citations to this article as recorded by
- Navigating the impact: a study of editors’ and proofreaders’ perceptions of AI tools in editing and proofreading
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Discover Artificial Intelligence.2024;[Epub] CrossRef - Beyond Plagiarism: ChatGPT as the Vanguard of Technological Revolution in Research and Citation
Hanni B. Flaherty, Jackson Yurch
Research on Social Work Practice.2024;[Epub] CrossRef - Recent Issues in Medical Journal Publishing and Editing Policies: Adoption of Artificial Intelligence, Preprints, Open Peer Review, Model Text Recycling Policies, Best Practice in Scholarly Publishing 4th Version, and Country Names in Titles
Sun Huh
Neurointervention.2023; 18(1): 2. CrossRef - Artificial intelligence-assisted medical writing: With greater power comes greater responsibility
Rhythm Bains
Asian Journal of Oral Health and Allied Sciences.2023; 13: 2. CrossRef - Emergence of the metaverse and ChatGPT in journal publishing after the COVID-19 pandemic
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Science Editing.2023; 10(1): 1. CrossRef - Author-Profile-Based Journal Recommendation for a Candidate Article: Using Hybrid Semantic Similarity and Trend Analysis
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IEEE Access.2023; 11: 45826. CrossRef - Utilization of artificial intelligence technology in an academic writing class: How do Indonesian students perceive?
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Journal of Educational Evaluation for Health Professions.2023; 20: 40. CrossRef - Current Status of Neurointervention, the Official Journal of the Korean Society of Interventional Neuroradiology
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Neurointervention.2022; 17(2): 67. CrossRef - Profiles of Technology Use and Plagiarism in High School Education
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SSRN Electronic Journal .2021;[Epub] CrossRef
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