Leveraging ScholarAI and GPT-4 for Efficient Research Synthesis: A Case Study on Creating a Literature Matrix

Research can be a time-consuming process, especially when it comes to gathering and analyzing academic papers. But what if I told you that Artificial Intelligence (AI) can help you cut corners without cutting quality? In this blog post, I’ll share how I used ScholarAI and ChatGPT-4 to create a literature matrix, making my research process faster and more thorough.

What Are ScholarAI and ChatGPT?

Before diving into the process, let’s get to know our main characters:

  • ChatGPT, developed by OpenAI, is a conversational AI model trained on diverse internet text.

  • ScholarAI is a plugin for ChatGPT-4 that uses its AI-powered platform to facilitate searching and retrieving open-access, peer-reviewed scientific literature.

GPT-4 can interact with ScholarAI to query, analyze, and summarize academic papers. It offers keyword-based search, sorting by citation count or publication date, and full-text retrieval.

How It Works: A Step-by-Step Guide

Step 1: Pick Your Keywords

Start by jotting down 4-6 keywords central to your research topic. You can see how I did this in Figure 1: I queried GPT-4 + ScholarAI with these keywords to retrieve abstracts of relevant papers. Note that the output is specified as a table, indicating the start of a literature matrix.

Figure 1. The original input into ChatGPT-4 with ScholarAI plugin

Step 2. Examine the Output

ChatGPT provided summaries and insights, allowing for a quick relevance assessment, as shown in Figure 2.

Figure 2. ChatGPT’s first output for the query shown in Figure 1.

Step 3. Determine overlooked sources

3a. Because of my familiarity with this body of literature, I recognized that at least one major source had been overlooked. So, I asked ChatGPT whether it was relevant. The ScholarAI plugin was useful for identifying this highly relevant paper, and GPT-4 added it to my literature matrix (Figure 3).

Figure 3. Asking for additions to the matrix based on research via other tools

3b. I double-checked GPT-4 + ScholarAI with the usual tools to find literature (e.g., Elicit.org, Scite.AI, and Google Scholar alongside my library database) and identified another citation. This underscores the need to use multiple tools to identify all potential sources.

Figure 4. Additions of more research to the matrix

The Perks

Speed: This AI combo can do in hours what would normally take you days. It’s like having a research team at your fingertips.

Depth: ChatGPT + ScholarAI doesn’t just skim the surface. It dives deep into the papers, picking up details you might miss.

The Catch: It’s not all sunshine and rainbows. The quality of your literature matrix depends on how well you interact with the AI and how well you can triangulate the use of other tools to fill gaps. While these tools are pretty smart, they’re not perfect. The optimal way to use them is in tandem with other tools and with your own human brain.

Wrapping Up

ScholarAI and ChatGPT make a powerful duo for speeding up the research process. They handle the heavy lifting so you can focus on what really matters: understanding and interpreting the information. Given how well this worked for me, I’m excited to see how it could be applied in other fields and research areas. So, if you want to give your research a turbo boost, why not try ScholarAI and ChatGPT?

Integrating ScholarAI and ChatGPT significantly reduced the time required for literature synthesis. What traditionally took days was accomplished in a matter of hours. The AI-driven approach enabled a more comprehensive review, as ChatGPT could quickly analyze and summarize large volumes of text, highlighting nuances that might be overlooked in manual reviews.

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