ArticleBrazilian oral research2026
Humanization of AI-generated abstracts in oral radiology: Role of chatbots and dedicated platforms.
Article in Brazilian oral research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
0 citing papers in PubMed.
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Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The rise of generative artificial intelligence (AI) in scientific writing has prompted the development of platforms designed to "humanize" AI-generated text by rephrasing content to reduce its detectability as machine-generated. This study aimed to evaluate the performance of chatbots and dedicated platforms in humanizing AI-generated abstracts. Thirty high-impact scientific articles published in dentomaxillofacial radiology journals were selected. The Methodology and Results sections of each abstract were used to prompt two chatbots-ChatGPT and Gemini-to generate complete abstracts. These AI-generated abstracts were then humanized using the same chatbots along with two dedicated platforms: HumanizeAI and StealthWriter. The percentage of AI-generated content was determined for all abstracts (n = 330), including the original human-written abstracts, using GPTZero. AI detection rates were compared using two-way analysis of variance followed by Tukey's post hoc test (α = 0.05). The results showed that original abstracts and AI-generated abstracts humanized by HumanizeAI and StealthWriter exhibited significantly lower GPTZero detection rates (p < 0.05), whereas abstracts generated or humanized by chatbots showed significantly higher detection rates (p < 0.05). In conclusion, chatbot-generated scientific abstracts humanized by dedicated platforms exhibit low AI detection rates, whereas those humanized by chatbots exhibit considerably higher detection levels. Educators must prepare students with critical appraisal skills to identify AI-generated content and uphold academic integrity, ensuring that AI serves as a complementary tool rather than a means of misrepresentation.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.