ChatGpt: Open Possibilities
Open accessAbstract
ChatGPT-3 is a powerful language model developed by OpenAI that has the potential to revolutionize the way weinteract with technology. This model has been trained on a massive amount of data, allowing it to understand andgenerate human-like text with remarkable accuracy. One of the most exciting possibilities of ChatGPT-3 is its potentialto improve natural language processing (NLP) and natural language understanding (NLU) in a wide range ofapplications. In particular, ChatGPT-3 can be used to power chatbots, virtual assistants, and other conversationalinterfaces. These types of systems are becoming increasingly important as more and more people use voice and text tointeract with technology, we list ChatGpt role in each of the follwoing sections
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
ChatGPT was listed in several sources as an efficient and promising tool for conducting comprehensive literature reviews and generating computer codes, thereby saving time for research steps requiring more human intelligence.
“Specifically, ChatGPT was listed in several sources as an efficient and promising tool for conducting comprehensive literature reviews and generating computer codes, thereby saving time for the research steps that require more efforts from human intelligence (e.g., the focus on experimental design) [14,27,28,41,44,46,47,60,71,72].”
From ChatGPT Utility in Healthcare Education, Research, and Practice: Systematic Review on the Promising Perspectives and Valid Concerns (2023) · cites this paper as [41]
Cites
Pavlik, J. V. (2023) · Journalism & Mass Communication Educator · doi:10.1177/10776958221149577 · Cited by 972 · cited 1× · see citing works
“These types of systems are becoming increasingly important as more and more people use voice and text to interact with technology, we list ChatGpt role in each of the follwoing sections[1].”
Background
Flagged first, then by citations
Cited by
Sorted by citations
Sallam, M. (2023) · Healthcare · doi:10.3390/healthcare11060887 · Cited by 3,126 · see citing works
“[41] An editorial on the possibilities provided by ChatGPT ChatGPT can help in academic writing; helpful in code generation Inaccurate content including inability handle mathematical calculations to reliably ChatGPT will receive a growing interest in the scientific community”
BackgroundSallam, M., Salim, N., Barakat, M., & Al-Tammemi, A. (2023) · Narra J · doi:10.52225/narra.v3i1.103 · Cited by 331 · see citing works
Better by You, better than Me? ChatGPT-3 as writing assistance in students’ essays.
Bašić, Ž., Banovac, A., Kružić, I., & Jerković, I. (2023) · doi:10.35542/osf.io/n5m7s · Cited by 189 · see citing works
Liu, W., & Wang, Y. (2024) · European Journal of Education · doi:10.1111/ejed.12804 · Cited by 153 · see citing works
Meyer, A., Riese, J., & Streichert, T. (2024) · JMIR Medical Education · doi:10.2196/50965 · Cited by 110 · see citing works
Tang, Q., Deng, W., Huang, Y., Wang, S., & Zhang, H. (2025) · Journal of Computer Assisted Learning · doi:10.1111/jcal.70027 · Cited by 55 · see citing works
Accelerating Software Development Using Generative AI: ChatGPT Case Study
Rajbhoj, A., Somase, A., Kulkarni, P., & Kulkarni, V. (2024) · Proceedings of the 17th Innovations in Software Engineering Conference · doi:10.1145/3641399.3641403 · Cited by 50 · see citing works
Factors influencing patients’ engagement with ChatGPT for accessing health-related information
Alanezi, F. (2024) · Critical Public Health · doi:10.1080/09581596.2024.2348164 · Cited by 26 · see citing works
Sallam, M. (2023) · doi:10.1101/2023.02.19.23286155 · Cited by 3,123 · see citing works
“…in several sources as an efficient and promising tool for conducting comprehensive literature reviews and generating computer codes, thereby saving time for the research steps that require more efforts from human intelligence (e.g., the focus on experimental design) [14,27,32,33,38,47,55,58,78,79].”
Method
- Authors
- Aljanabi, M., Ghazi, M., Ali, A. H., Abed, S. A., & ChatGpt
- Affiliations
- Iraqi University (IQ)
- OpenAI (United States) (US)
- ORCID
- Mohammad Aljanabi
- Venue
- Iraqi Journal for Computer Science and Mathematics
- Published
- 2023-01-18
- Pages
- 62-64
- ISSN
- 2788-7421 (ISSN-L)
- OpenAlex
- W4318466538
- Cited by
- 91
- References
- 1
- Citations by year
- 2026: 3 · 2025: 8 · 2024: 37 · 2023: 42 · 2022: 1
- FWCI
- 7.97
- Type
- journal article
- Language
- en
- Open access
- diamond
- doi.org
- Licence
- cc-by
- Locations
- Iraqi Journal for Computer Science and Mathematics (publishedVersion, cc-by)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Topic Modeling
- Physical Sciences › Computer Science › Artificial Intelligence › Speech and dialogue systems
- Physical Sciences › Computer Science › Artificial Intelligence › Natural Language Processing Techniques
- Keywords
- ChatGPT-3, large language models, natural language processing, natural language understanding, chatbots, virtual assistants, conversational interfaces
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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