Scientific novelty beyond the experiment

Abstract

Practical experiments drive important scientific discoveries in biology, but theory-based research studies also contribute novel-sometimes paradigmchanging-findings. Here, we appraise the roles of theory-based approaches focusing on the experiment-dominated wet-biology research areas of microbial growth and survival, cell physiology, host-pathogen interactions, and competitive or symbiotic interactions. Additional examples relate to analyses of genome-sequence data, climate change and planetary health, habitability, and astrobiology. We assess the importance of thought at each step of the research process; the roles of natural philosophy, and inconsistencies in logic and language, as drivers of scientific progress; the value of thought experiments; the use and limitations of artificial intelligence technologies, including their potential for interdisciplinary and transdisciplinary research; and other instances when theory is the most-direct and most-scientifically robust route to scientific novelty including the development of techniques for practical experimentation or fieldwork. We highlight the intrinsic need for human engagement in scientific innovation, an issue pertinent to the ongoing controversy over papers authored using/authored by artificial intelligence (such as the large language model/chatbot ChatGPT). Other issues discussed are the way in which aspects of language can bias thinking towards the spatial rather than the temporal (and how this biased thinking can lead to skewed scientific terminology); receptivity to research that is non-mainstream; and the importance of theory-based science in education and epistemology. Whereas we briefly highlight classic works (those by Oakes Ames, Francis

ChatGPT Utility in Healthcare Education, Research, and Practice: Systematic Review on the Promising Perspectives and Valid Concerns

“…Such a practice can be acceptable considering the already existent English editing services provided by several academic publishers. Subsequently, this can help to promote equity and diversity in research [ 46 , 55 ].…”

“…First, superficial, inaccurate, or incorrect content was frequently cited as a shortcoming of ChatGPT use in scientific writing [ 14 , 28 , 29 , 40 , 60 ]. The ethical issues including the risk of bias based on training datasets and plagiarism were also frequently mentioned, aside from the lack of transparency regarding content generation, which justifies the description of ChatGPT, on occasions, as a black box technology [ 14 , 25 , 26 , 40 , 44 , 45 , 46 , 47 , 48 , 55 , 60 , 63 , 65 , 72 ]. Importantly, the concept of ChatGPT hallucination could be risky if the generated content is not thoroughly evaluated by researchers and health providers with proper expertise [ 37 , 56 , 73 , 77 , 79 ].…”

The Utility of ChatGPT as an Example of Large Language Models in Healthcare Education, Research and Practice: Systematic Review on the Future Perspectives and Potential Limitations

“…On the other hand, the use of ChatGPT in academic writing and scientific research should be done in light of the following current limitations that could compromise the quality of research: First, superficial, inaccurate or incorrect content was frequently cited as a shortcoming of ChatGPT use [14,47,49,77,79]. The ethical issues including the risk of bias based on training datasets, and plagiarism were frequently mentioned, besides the lack of transparency described on occasions as a black box technology [14,27,[29][30][31][32][33]35,36,39,57,58,77,79]. Importantly, the concept of ChatGPT hallucination was mentioned which can be risky if not evaluated properly by researchers and health providers with proper expertise [59,60,65,73,74].…”

The Utility of ChatGPT as an Example of Large Language Models in Healthcare Education, Research and Practice: Systematic Review on the Future Perspectives and Potential Limitations

“…On the other hand, the use of ChatGPT in academic writing and scientific research should be done in light of the following current limitations that could compromise the quality of research: First, superficial, inaccurate or incorrect content was frequently cited as a shortcoming of ChatGPT use [14,47,49,77,79]. The ethical issues including the risk of bias based on training datasets, and plagiarism were frequently mentioned, besides the lack of transparency described on occasions as a black box technology [14,27,[29][30][31][32][33]35,36,39,57,58,77,79]. Importantly, the concept of ChatGPT hallucination was mentioned which can be risky if not evaluated properly by researchers and health providers with proper expertise [59,60,65,73,74].…”

“…Sixth, legal issues were raised by several records as well, including copyright issues [14,27,57,73,75]. Finally, the issue of listing ChatGPT as an author does not appear acceptable based on the current ICMJE and COPE guidelines for determining authorship as illustrated by Zielinski et al and Liebrenz et al [25,36].…”