The Library has already subscribed to Scite, a powerful AI research tool designed to elevate your research experience.
Our subject guide, “AI Tools for Your Research: Scite” explains its features and provides instructions for getting started. Recently Scite has launched a new feature, Tables in Scite Assistant, a major advancement that enables researchers to extract, organize and analyze data from scientific literature.
How to Use AI Tables?
Scite's AI Tables do more than just summarize papers—they help you extract specific data points, methodologies, and outcomes directly from scientific articles.
Step 1: Go to Scite Assistant and select “Use Table Mode” for the new Table function.

Step 2: Click “Add Column” and type “name” and “instructions” for the new column. You can choose the length of the answers, from short to long.


Step 3: Continue creating new columns, such as “Methodology,” “Key Findings,” and others, to organize and analyze your data effectively.

In addition, you can export all references with all columns in various formats, such as CSV, ris and BibTeX.
New Improvements to Scite Assistant
OpenAI o3 mini + Reasoning
A new AI model, OpenAI o3 mini, now integrates advanced reasoning capabilities and is being utilized by Scite. Scite enhances its platform by combining its own datasets and access to scholarly content with powerful AI models, offering researchers tools for analysis and discovery.
What is “Reasoning”?
Reasoning Models: These are advanced AI systems that go beyond simple pattern recognition (which is what most standard AI models do). Instead, they are designed to:
- Think through problems internally before answering.
- Consider multiple approaches to solving a question.
- Evaluate the accuracy of different possible answers.
- Plan structured and coherent responses.
- Solve multi-step problems methodically.
Highlight Summary
EBSCO now provides a Natural Language Search mode that uses LLMS to allow you to search using everyday language. It understands what you’re looking for, even if you ask in full sentences, and it delivers better results.
How Does Natural Language Search Work?
Natural Language Search (NLS) lets you search the way you naturally speak or write—no need for special keywords or complicated search rules. No need to use the complex keywords or Boolean operators, for example, you can ask the question "What is the best education for children?" instead of using (education OR schooling) AND (child* OR kid* OR student* OR pupil*) AND (best OR optimal OR effective) AND ("academic achievement" OR outcomes OR “learning results”).
Here is the comparison table of Traditional Search vs. Natural Language Search:
Traditional Search
Natural Language Search
How to Use Natural Language Search Mode?
STEP 1: Go to “Advanced Search Mode” from the basic search.
STEP 2: Under “Search options”, you can select “Natural language” to turn on this mode.
STEP 3: To turn on NLS mode immediately, simply toggle the Natural Language switch in basic search.
Step 4: Now let's test NLS mode with our sample question: “What is the best education for children?” Observe how NLS generates 810,595 comprehensive results while the traditional search generates a limited 250 records.
You'll notice that the NLS mode retrieves relevant results containing conceptually related terms, such as “teaching”, “effective”, and “students”—even though these exact words weren't included in our original search query. This demonstrates a key advantage of Natural Language Search: unlike traditional keyword-based systems, NLS leverages Large Language Models (LLMs) to interpret the semantic meaning behind your question, eliminating the need for exact keyword matching.
Recommendations from the Library:
To get the most out of EBSCO's search tools, the following strategies for combining NLS and traditional search mode are: