The creation of chatbots, such as Generative Pre-trained Transformer (GPT), is a result of recent developments in natural language processing (NLP). Even though Chat GPT has demonstrated enormous ...promise in a number of areas, including scientific research, this impact is still developing. This paper attempts to investigate the possibilities, threats, limits, and ethical issues surrounding Chat GPT in scientific research. The assessment of the literature on Chat GPT and scientific research is followed by the presentation of case examples that demonstrate the potential advantages and difficulties of Chat GPT use in scientific research. Finally, we conclude by pointing about the ethical issues that need to be tackled before Chat GPT can be completely utilized in scientific research.
The current study aims to establish a connection between students' behavioral concerns, namely stress and anxiety, related to the completion of academic tasks, and their integration of technology ...using the Technology Acceptance Model (TAM) through the utilization of Chat-GPT via ubiquitous learning (UL) procedure. To achieve this objective, data was collected from 156 students studying management science who were engaged in their final year research projects or internship reports from selected universities in Pakistan. The gathered data underwent analysis through Structural Equation Modeling (SEM) using Smart PLS software. The findings reveal a significant relationship: students' stress contributes to the emergence of anxiety, which in turn motivates the adoption of technology-assisted solutions, specifically Chat-GPT, to efficiently complete assigned tasks within deadlines working through any device from anywhere. Consequently, the perceived ease of use and usefulness associated with Chat-GPT's AI-generated text contribute to shaping students' favorable attitudes toward utilizing Chat-GPT and also play a role in reducing their stress levels. Furthermore, the study confirms that the development of a positive attitude in students acts as a driving force, compelling them to engage with Chat-GPT through ubiquitous learning (UL) procedure, ultimately resulting in increased actual usage of Chat-GPT. This pattern, in turn, contributes to stress and anxiety reduction among management science students. The study's outcomes corroborate the TAM model, which aligns with the social exchange process, demonstrating its applicability within the context of the educational setup in management sciences and its potential to enhance the learning experiences of researchers.
•The study applies the Technology Acceptance Model to understand chat-GPT use among students of Universities of Pakistan.•Psychological factors (stress & Anxiety) and technology use is investigated among university students.•Behavioral Factors, Ubiquitous learning, Chat GPT and TAM are aligned to understand human computer interaction.•Based on detail analysis novel approach related to Technology and Social Acceptance Model (TSAM) is proposed.
Background: Hepatitis B is the main infection of the injured liver for humans. Inflammation of the liver is caused by hepatitis viruses may lead to cirrhosis and hepatocellular carcinoma. The B-cell ...stimulatory factor 2 (BSF-2) is one of the cytokines that affect the regulation and differentiation of the human immune response. Objective: this report aims to estimate the BSF-2, GPT, and GOT levels in patients’ serum with different stages of hepatitis B compared with healthy control. Methods: This study assessed 52 patients presumably with acute and chronic cases who have HBsAg positive. BSF-2 was detected using ELISA assay. Biochemical parameters were determined using kits of an automated analyzer. SPSS version-16 software was used for statistical analysis. Results: Acute hepatitis B patients had shown elevation in BSF-2 level more than of chronic hepatitis B. GPT and GOT levels elevated in the acute hepatitis group more than of the chronic hepatitis group. We reported a significant value between BSF-2, GOT, and GPT levels. We didn’t score an association between patient’s age and cases groups of hepatitis. Conclusion: our data confirmed increasing of BSF-2 levels with the increase of GOT level more than GPT level with acute hepatitis B. BSF-2, GPT and GOT levels are varied in different courses of acute and chronic HBV. We surmised that the elevation of BSF-2 levels designates liver injury of patients with acute HBV.
The systematic review of clinical research papers is a labor-intensive and time-consuming process that often involves the screening of thousands of titles and abstracts. The accuracy and efficiency ...of this process are critical for the quality of the review and subsequent health care decisions. Traditional methods rely heavily on human reviewers, often requiring a significant investment of time and resources.
This study aims to assess the performance of the OpenAI generative pretrained transformer (GPT) and GPT-4 application programming interfaces (APIs) in accurately and efficiently identifying relevant titles and abstracts from real-world clinical review data sets and comparing their performance against ground truth labeling by 2 independent human reviewers.
We introduce a novel workflow using the Chat GPT and GPT-4 APIs for screening titles and abstracts in clinical reviews. A Python script was created to make calls to the API with the screening criteria in natural language and a corpus of title and abstract data sets filtered by a minimum of 2 human reviewers. We compared the performance of our model against human-reviewed papers across 6 review papers, screening over 24,000 titles and abstracts.
Our results show an accuracy of 0.91, a macro F
-score of 0.60, a sensitivity of excluded papers of 0.91, and a sensitivity of included papers of 0.76. The interrater variability between 2 independent human screeners was κ=0.46, and the prevalence and bias-adjusted κ between our proposed methods and the consensus-based human decisions was κ=0.96. On a randomly selected subset of papers, the GPT models demonstrated the ability to provide reasoning for their decisions and corrected their initial decisions upon being asked to explain their reasoning for incorrect classifications.
Large language models have the potential to streamline the clinical review process, save valuable time and effort for researchers, and contribute to the overall quality of clinical reviews. By prioritizing the workflow and acting as an aid rather than a replacement for researchers and reviewers, models such as GPT-4 can enhance efficiency and lead to more accurate and reliable conclusions in medical research.
Climate change is a major global challenge that requires the integration of many different scientific disciplines, including atmospheric science, oceanography, and ecology. The complexity and scale ...of the problem require sophisticated tools and techniques to understand, model, and project future climate conditions. Artificial intelligence and natural language processing technologies, such as ChatGPT, have the potential to play a critical role in advancing our understanding of climate change and improving the accuracy of climate projections. ChatGPT can be used in a variety of ways to aid climate research, including in model parameterization, data analysis and interpretation, scenario generation, and model evaluation. This technology provides researchers and policy-makers with a powerful tool for generating and analyzing different climate scenarios based on a wide range of data inputs, and for improving the accuracy of climate projections. The author acknowledges asking chatGPT questions regarding its uses for Climate Change Research. Some of the uses that it states are possible now and some are potentials for the future. The author has analyzed and edited the replies of chat GPT.
The use of transformer‐based language models in artificial intelligence (AI) has increased adoption in various industries and led to significant productivity advancements in business operations. This ...article explores how these models can be used to augment human innovation teams in the new product development process, allowing for larger problem and solution spaces to be explored and ultimately leading to higher innovation performance. The article proposes the use of the AI‐augmented double diamond framework to structure the exploration of how these models can assist in new product development (NPD) tasks, such as text summarization, sentiment analysis, and idea generation. It also discusses the limitations of the technology and the potential impact of AI on established practices in NPD. The article establishes a research agenda for exploring the use of language models in this area and the role of humans in hybrid innovation teams. (Note: Following the idea of this article, GPT‐3 alone generated this abstract. Only minor formatting edits were performed by humans.)
PDF
