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It has been nearly 30 years since I published my first scientific paper. During my time as a PhD student in Germany, I had the privilege of learning this algorithm from an exceptional mentor, mein Herr Professor, and a seasoned PhD colleague from Sauerland who became a dear friend and even turned me into an Eintracht Frankfurt fan. He patiently guided me through the intricate technicalities of the machinery, the calligraphy, and the nuances of our “chef’s” expectations, all while imparting a profound understanding of the underlying physics behind our theories. As my German friends often say, ‘Alle Anfang ist schwer‘ (All beginnings are difficult). And indeed, the process of producing that initial scientific paper was anything but easy.
Today, with nearly 100 published papers and book chapters to my name (including one for Springer), I don’t fit the stereotype of a verbose scientist. Instead, I prioritize crafting well-written and cohesive papers, collaborating closely with a select group of colleagues to thoroughly explore a subject, or at least I try hard. I owe much of this approach to the guidance and teachings of my German mentors. Rather than churning out numerous fragmented preliminary papers for conferences and various scientific journals, accompanied by a multitude of co-authors I hardly know, all in pursuit of sheer numbers for funding agencies, I have long liberated myself from that enslaving process. Everything I do now is driven by passion and enjoyment.
Allow me to share an example that highlights this shift. During my second stint as a post-doc in Germany, I authored a 14-page theoretical and experimental paper. Rather than breaking it into several smaller papers for the sake of numbers, I kept it intact as a comprehensive masterwork. I am immensely grateful to the small number of collaborators involved (a wonderful couple of theoretical physicists) and my supportive and brilliant supervisor at that time, who also happens to be a dear friend.
The process of producing a scientific publication is undeniably challenging, as I previously mentioned. The initial stages are particularly arduous, and the difficulties are compounded for non-native English speakers hailing from South American countries like Brazil. Furthermore, if you find yourself outside the limited domains of knowledge within reputable public universities, the obstacles become even no less formidable as for the greenhorns. The involvement of funding agencies and university burocracy with their flawed metrics and the constantly shifting political ideologies can transform the early career of an aspiring scientist into a nightmarish ordeal. I have witnessed several exceptionally talented individuals leave for the United States and Europe due to insufficient stipends that failed to cover their basic expenses, ultimately ensuring that they would never return. They are acutely aware that professorial positions in esteemed universities within our country are also inadequately remunerated. On top of the challenges associated with securing such positions, surviving the bureaucratic red tape, politics, and various other impediments proves to be incredibly demanding. If one is fortunate enough to obtain the opportunity to teach prestigious courses, they often yearn for an environment where they can delve into their studies, flourish, and embody a reservoir of wisdom and knowledge to benefit the forthcoming generations.
Well, after three paragraphs discussing the challenges of academia, you might be curious about the role of AI. The answer is quite straightforward. Just as our academic careers are impacted by external bureaucracies that exist beyond the confines of labs and classrooms, as well as internal politics (and nasty ideologies) within coffee rooms (which have now been rendered empty due to the COVID-19 pandemic, replaced by ceaseless email exchanges on official mailing lists), our scientific lives are further burdened by unproductive tasks. However, the emergence of the Artificial Intelligence revolution offers a promising solution to these challenges.
The same machine learning algorithms that will assess, evaluate, interview, and classify graduate students, even adapting their assessment criteria (referred to as “barema” in Portuguese, a somewhat ridiculous word but an amazing concept) into simple weights and biases within neural networks, and allocate scholarships among them (what a simple NN would be, and what a large amount of data it could be trained with), will also serve as peer reviewers for scientific publications. Its is amazing how much time it will spare, how much unecessary jobs can be cut and how much our own salary could grow with these cuts (ok I am provoking, I could not hold myself at this). I still ought to make one NN for that, just for fun and publicize the python code for free here, what about an article like AI “baremates” and pick the best graduate students using data correlations hidden for human eyes evaluators?
Although this new technology may not yet possess the cognitive ability to interpret graphs, tables, and equations (there are already excellent AI Co-pilot tools available to assist with that), it can be valuable in assisting with language correction in papers, which is often a tedious task. Referees, who may not fully grasp the meticulous work presented in the paper, often place emphasis on the language aspect and feel obliged to provide feedback to the editors rather than declining by simply stating, “I lack the necessary knowledge to review it, sorry…”.
Furthermore, natural language processing can accomplish remarkable feats and save you a significant amount of time. Let’s consider ChatGPT, for example. By visiting the OpenAI.com website, you can register and log in using any Gmail account. And voilà! You can utilize GPT-3, the powerful and free alternative to the fancy, paid GPT-4 (or the slower free version from Bing). With the impressive GPT-3 and its grey night mode, you can simply copy the title of the paper, the abstract, and the lengthy sequence using ‘Ctrl+C’ and ‘Ctrl+V’ from a PDF or Word document into the prompt (although this process can still be tedious if you haven’t yet automated it with an AI Co-pilot). Of course, you need to include the prompts before the text. What makes it truly marvelous is working with the prompts—GPTs can even tailor them to your needs. The better the prompt engineering the most accurate are the answers. Below is a short list of ten prompts you can use to review your next paper.
Prompt> Please provide 10 prompts for an editor and reviser conducting a language, grammar, clarity, and organization review of a scientific paper.
Answer> Certainly! Here are 10 prompts for an editor and reviser of a scientific paper regarding language, grammar, clarity, organization, and more:
- Evaluate the overall clarity and coherence of the paper. Are the ideas presented in a logical and organized manner? Is the flow of information smooth and easy to follow?
- Review the abstract and introduction. Do they effectively summarize the paper’s purpose, objectives, and main findings? Are they engaging and concise?
- Check the language and grammar throughout the paper. Are there any sentence structure issues, awkward phrasings, or grammatical errors that need correction?
- Assess the use of scientific terminology. Is the terminology accurate and appropriately used? Are there any instances where technical terms need to be defined or clarified for the readers?
- Examine the consistency of formatting and style. Ensure that headings, subheadings, citations, and references adhere to the required style guide (e.g., APA, MLA, Chicago).
- Verify the accuracy of citations and references. Cross-check in-text citations with the reference list to ensure proper citation format and accuracy.
- Analyze the clarity of figures, tables, and graphs. Do they have clear labels, titles, and captions? Are they easy to interpret? Check if the data presented is accurate and supports the main points (Here you will need a Co-Pilot…).
- Assess the use of transitions between paragraphs and sections. Are there smooth transitions that guide the reader through the paper? Do they effectively connect ideas and maintain coherence?
- Consider the overall word choice and tone of the paper. Is the language precise, concise, and appropriate for a scientific audience? Are there any instances where the tone needs adjustment?
- Evaluate the conclusion section. Does it effectively summarize the main findings and their implications? Is the conclusion supported by the evidence presented in the paper?
These prompts can serve as a valuable guide for the editor and reviser to ensure that the scientific paper adheres to high standards of language, grammar, clarity, organization, and overall readability.
As a reviser for various scientific journals, I have implemented these prompts in my last review with great success. While it is true that authors may have additional work to improve the language, the overall quality of the paper is significantly enhanced thanks to AI. It is important to note that the language revision work is only half of the task. The editors could also perform initial language corrections with AI before sending the paper for review. This allows us to focus on providing suggestions and corrections that truly matter, specifically the scientific content.
I hope I have successfully conveyed the significance of AI in revolutionizing the landscape of some specific academic tasks and scientific tedious work. The integration of AI technologies brings forth transformative opportunities, opening up new possibilities and streamlining various aspects of the scientific process. Despite its tremendous potential, it is natural for some individuals to exhibit hesitancy in embracing this change. Ah those luddits! The familiar routines and established practices that have characterized the scientific community for years can create resistance to adopting novel approaches.
It is important to recognize that change can be unsettling, and it may take time for individuals to fully comprehend and appreciate the benefits that AI can offer. Moreover, the intricacies and nuances of scientific research require a delicate balance between human expertise and the capabilities of AI. While AI can undoubtedly enhance efficiency and accuracy in certain areas, it is essential to maintain the critical thinking and creativity that human scientists bring to the table.
As we move forward, it will be fascinating to witness how the scientific community evolves and adjusts to the integration of AI. Only time will reveal the extent to which AI transforms academic and scientific research practices and whether my perspective regarding its potential impact holds true. With ongoing advancements and continued exploration of AI’s capabilities, it is an exciting era for scientific discovery, one that holds the promise of accelerating progress and expanding the boundaries of knowledge.
Now, if you’ll excuse me, I have a paper to review. It’s a nice sunny day outside on this public holiday, but my swimming pool and beer will have to wait.
Best regards,
Maurício Pinheiro
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