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The study aims to investigate the influence of HIX.AI, an artificial intelligence (AI) tool that humanizes the generated content, on the detection capabilities of AI-generated text detectors.

The study investigates the reliability of six AI-generated content detection tools by passing ten essays, five each generated using Chat Generative Pre-Trained Transformer (ChatGPT) and Bard (Gemini) before and after passing through HIX.AI, which humanizes the AI-generated content.

The study found that the selected AI-generated text detectors identified the generated content with inconsistencies. Some of the essays were falsely identified as human-written by a few detectors, indicating that the detectors are unreliable. Post-HIX.AI application found that all the essays were passed as human-written except two, which identified as AI-generated and mixed content by two separate detectors.

The findings present the evolving field of AI-generated text detectors and the tools that can bypass the detectors highlighting the difficulties in identifying the generated content in the presence of the humanization tool. Passing the generated content as human-written has serious consequences, especially in academics. Hence, the study recommends more robust detectors to distinguish human-written and AI-generated content accurately.

The study contributes to the existing literature on AI text detectors and highlights the challenges that humanization tools pose in identifying AI-generated text by AI text detectors.

This paper aims to delve into the critical examination of retractions in virology to identify the underlying factor that led to the retraction of scientific publications in this specialised domain. Further, this study offers insights into the impact of the retracted publications in the scholarly world vis-à-vis citation and Altmetric indicators.

The top 100 highly cited retracted articles from virology category were taken from the Web of Science (WoS) database. The Retraction Watch database was used for knowing the reasons for retraction for each retracted publication. The citation and Altmetric score of retracted publications were noted down from WoS and Altmetric.com databases, respectively. Journal Citation Report was used to note down the impact factor of the journals that have published these articles.

“Misconduct” (57.73%) is the most prevalent reason for the retraction of publications followed by plagiarism (18.55%) and journal issues (14.43%). The retracted papers are cited even after their retraction. Around 70.52% citations were received before and 29.47% after retraction. The highest number of retracted papers was published in the Journal of Virology (14) and Journal of Chemistry (10). High-impact factor journals such as Lancet, Cell and Nature each own one retracted paper. The study found dissemination of these publications through social media platforms with highest social media mentions (394) followed by policy and patents mentions (373) and news and blog mentions (300).

The research delves into understanding the reasons behind the retraction of virology papers and the impact of these publications through citation and Altmetric analyses. Its impactions include bolstering quality control in virology research, maintaining trust in scientific literature. Citation and Altmetric analyses offer deep insights into the broader impact of retracted papers, informing policy and publishing practices to uphold scientific integrity in virology.

This study addresses a specific and crucial aspect of scientific research retractions within the field of virology. While retractions have been studied in broader terms in scientific research, to the best of the authors’ knowledge, no such study has been conducted in the scientific field of virology.