AI tools for finding scientific sources

Table of contents

AI assistants that are integrated into various scientific databases or AI applications linked to citation datasets can help you to find scientific sources: peer-reviewed journal articles, books from scientific publishers, conference papers, and preprints.

Such applications understand natural language, so you can search for sources by asking a question, describing your research topic, or copying text you have written into the search. In some applications, the search is based on a key research article (“seed paper”) that you have found previously. Applications utilize, for example, semantic or vector search and natural language processing (NLP) to enhance search functions, form search queries on behalf of the user, determine the relevance of sources, and find semantically similar sources. In addition to searching for scientific sources, these assistants and applications often summarize and classify information found in sources using generative AI.

Typically, such assistants and applications are user-friendly and have intuitive interfaces. They work best in English and for searching English-language sources, but some also support searches made in Finnish.

Applications provide a link to the source if it is openly available. Otherwise, for example, the full texts of published journal articles can be searched separately from the “International Articles search” tab in JYKDOK.

Benefits of AI assistants:

  • Interdisciplinarity – AI searches can bridge gaps between different scientific fields by finding connections and integrating information from various disciplines, thus providing search results that are not immediately apparent.
  • Natural language searching – The quality of search results does not depend on the user's ability to define the correct keywords and master the search syntax of different databases before conducting a search.
  • Creativity – Search results may include sources that might be surprising at first glance but offer new insights for research.

Weaknesses of AI assistants:

  • Relevance of search results – Key search results relevant to the topic may be missing from the results, unlike if the search were conducted in a specialized scientific database or Google Scholar.
  • Coverage of search results – AI assistants and applications may have access to a very limited amount of citation data and bibliographic references. They may only search openly available sources, sources indexed by their partners, or they may lack access to the most recent publication references. The same applies to more traditional database searches: to obtain comprehensive search results, searches often need to be conducted in multiple databases.
  • Opacity of search results – The user has less control over the search results compared to a Boolean search conducted in a scientific database. It is not always clear why the assistant or application offers certain search results and on what basis it assesses the relevance of the source.

For these reasons, if you are aiming for a systematic, comprehensive (sensitive), precise, and replicable search for your literature review, for example, your primary search method should be database searches using keywords / Boolean search. However, as a complementary method of information retrieval, AI assistants and applications are worth trying.

Keenious

  • Licensed and recommended by the Ģֱ!
  • is a tool utilising LLMs and vector search for finding scientific sources.
  • Keenious is best for exploring new topics, multidisciplinary information seeking, and supporting scientific writing.
  • If Keenious asks you to sign in, use either your university email address or JYU Microsoft two-step authentication.
  • Keenious works both in the browser and as an add-in in M365 Word.
  • Keenious does not save the texts you input, nor does it use them for AI training.
  • Keenious retrieves its search results from OpenAlex - a platform indexing research literature. 
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How to use in a browser

Select on the homepage: Text - Copy and paste text relating to the topic you want to find sources for into the text field.

Select on the homepage: PDF / URL - Upload a “seed paper” to Keenious, such as an article related to a topic you want to know more about. You can upload the paper in PDF format or open up the PDF in your browser and provide the URL address. You can also upload your own text in PDF format.

Cross-language

  • If cross-language is selected, you can search for English articles using a source text or seed paper in some other language, such as Finnish. In this case, Keenious will first translate the Finnish source text into English using Microsoft Azure.
  • If you want to search for English articles using English text, switch the cross-language feature off.
  • You can do 10 cross-language searches per day.

Highlight search

  • Typically, Keenious searches for sources based on your entire text document. However, if you wish, you can narrow the search to a specific part of the text or a particular concept. Keenious will then perform the search on the selected topic or concept within the context of your text document.
  • Select the desired part of the text or a concept > a “Highlighting text” bubble will appear on the right > click the magnifying glass icon in the bubble to perform the highlight search.

Articles tab

  • You will see a list of publications related to your text > click on an interesting publication > you will see the article’s abstract, authors, topics, citation counts (Cited by), and a list of similar articles.
  • Check JYU access: Check if the article is available in the JYKDOK databases (or Finna / Melinda).

Narrow down your search

  • By publication date: Filters > Year published
  • By citation count: Filters > Citation count

Search for more precise results using keywords or a search phrase

  • Enter keywords or a search phrase constructed with Boolean operators into the Search articles field.
  • The search field supports the operators AND, OR, and NOT; phrase search " "; and grouping of search phrases with parentheses ().

Topics tab

  • You will see a list of topics related to your text. By clicking on them, you will find sources related to the selected topic and get to explore the topic and its terminology more deeply.
  • You can filter sources by one or more topics by clicking the Filter results by this topic icon (three horizontal lines) and selecting either “Add to include list” or “Add to exclude list.”

How to use in M365 Word

Install the Keenious add-in in your JYU Microsoft 365 Word

  • Open a new Word document file.
  • Click Add-ins.
  • Search Add-ins > Keenious Research Explorer > Add

Open the text document you are working on.

  • Open Keenious in the sidebar.
  • Select Explore using text.
  • The search functions are the same as in the browser version. 

Note: If you select Explore using PDF, you will be redirected to the browser version of Keenious.

AI assistants in databases

ProQuest Research Assistant

  • AI Research Assistant is integrated into many databases on the ProQuest platform, supporting you in searching for scientific sources and summarizing articles. With the assistant's support, you can also familiarize yourself with the main concepts of articles and brainstorm related research topics.

How to use

  • Use to access a database on the ProQuest platform, for example, ProQuest Central.
  • Perform a search using a keyword/Boolean search phrase.
  • Filter search results to include only those with full text.
  • At the top of the search results page, you will find AI-recommended keywords to expand or refine your search. Keyword suggestions are not necessarily generated for all searches.
  • Select a publication of interest from the search results and click to open the reference details. If the publication includes full text, the Research Assistant will open on the right side of the page.

Searching for sources

  • Use the magnifying glass icon to search for related sources.
  • Search using indexing terms
    • Perform a search using generated subject keywords.
  • Explore suggested sources
    • Find other similar publications.

Familiarizing yourself with the publication and its main concepts

  • Here is the key takeaway
    • A brief summary of the publication.

Ready-made prompts:

What are the findings or conclusions?

Brainstorm related research topics.

Describe the important concepts.

  • Research Assistant generates a summary of the publication and answers to ready-made prompts based on the full text. Always verify the generated answer with the full text to ensure accuracy.
  • Remember that the generated answer is not a scientific source. If you want to cite the publication, you must read the publication yourself.
  • With the help of Research Assistant, you can also familiarize yourself with, for example, Finnish-language publications. Note that answers to ready-made prompts are generated in English, and key concepts from the publication may be incorrectly translated into English.

EBSCO Natural Language Query

  • Licensed and recommended by the Ģֱ!
  • Natural Language Query is an AI-assistant integrated into databases on the EBSCO platform, supporting you in your search for scientific sources.

How to use

  • Access EBSCO platform databases - such as PsycINFO, Business Source Elite, and eBook Collection - through . 
  • Basic search: switch on Natural language search.
  • Advanced search: open the tab Search options > Choose Natural language search.

Write a research question, research topic, or request in English on the search bar. For example: "What are the effects of austerity measures on consumers?"

  • EBSCO AI-assistant turns your natural language query into a Boolean search phrase. To review the search phrase, click Show refined query on the top of the search results page.

Dimensions

  • Licensed and recommended by the Ģֱ!
  •  is a multidisciplinary and large database containing references to scientific publications, policy documents, and research data, as well as information on received research funding, patents, and ongoing/completed clinical trials.
  • Access Dimensions through JYKDOK.
  • The reference data in Dimensions is collected directly from publishers and databases such as Crossref and PubMed Central, as well as other open sources. The references are not specifically curated, so it is always advisable to assess the quality and reliability of the sources yourself.
  • Dimensions also contains some full texts, and scientific publications found in Dimensions can also be searched in JYKDOK using the SFX link.
  • Dimensions utilizes artificial intelligence extensively. For example, reference data is enriched with AI-generated classifications and information. Additionally, several AI features have been developed to facilitate the use of the database

How to use

Natural language query

  • Look for a star symbol on the top navigation bar and click it.
  • You will receive a Boolean search phrase and filters for your query, which you can then use to complete your search in Dimensions.

Type your request, for example: "Find academic papers published in the past 5 years in the field of International Relations focusing on the Gramscian hegemony theory."

  • Note: this is a beta version, and at the time of testing, does not generate as complex and extensive Boolean search phrases as many generative AI chatbots do.

Summarize

  • The "Summarize" button is available both within the search results list and when accessing an individual reference.
  • This feature generates a TL;DR summary, Key highlights of the paper, and lists Top keywords you can use to continue your search.

Chat with PDF

  • Chat with PDF differs from the other two AI features, as it is not directly integrated into the Dimensions database. Instead, it requires the use of a free version of an application called Papers, for which you need to create a user account.
  • The Chat with PDF button is available both within the search results list and when accessing an individual reference. You will be redirected to the Papers application in your browser, where you need to Register (Try Papers for FREE) or Sign in (Sign into an existing Papers account) if you already have an account.
  • (Step 1: Download from publisher > Go to publisher) Download the PDF file of the publication from the publisher's website to your computer > (Step 2: Upload downloaded PDF) Upload the PDF to the application.

You can ask the Papers AI assistant any questions regarding the article's content. Inquiries may include the research methodology, main findings, or definitions of concepts. For example: What does energy justice mean in the context of this paper?

  • You will receive a generated response to your question, along with links to the relevant sections of the publication used by the AI assistant to generate its response.

Semantic Scholar

  • is a multidisciplinary database indexing scientific publications.
  • Free.
  • Creating a user account is not mandatory.

How to Use

Search with your research topic or keywords, for example: text data mining methods. 

  • You can use natural language and also do your search in Finnish if you are looking for Finnish sources.

Search results page:

  • List of relevant sources.
  • TLDR (Too Long; Didn’t Read): a brief summary of the publication’s main goals and results.
  • You can filter results by discipline and publication time.
  • Click open a reference that interests you.

Reference page:

  • TLDR summary
  • Figures and tables
  • Citations: publications citing the paper.
  • References: the paper’s bibliography.
  • Cite: save citation information in different citation styles.
  • Highly influential citations: publications significantly influenced by the selected paper.
  • Related Papers: similar publications.
  • Topics: related topics > Go to a separate Topic Page Beta for more information on the topic, frequently cited publications, and the latest articles on the topic (Definition, Related Topics, Papers often cited for this topic; Recent papers on this topic).
  • Note that not all references contain the above information!

Additionally, Semantic Scholar offers the following features for some papers:

  • Ask a question about > ask questions related to the paper, the language model provides answers based on the paper, justifies the answers with references, and indicates the page number.
  • Semantic Reader > Find the paper’s essential points - Goals, Methods, Results - faster with automatic highlighting.

When logged in, you can:

  • Save and sort search results into folders.
  • Find relevant sources using references saved in folders.
  • Create public folders and share collected references with colleagues.
  • Enable AI-generated publication recommendations (Research Feed).
  • Enable notifications (Paper Alerts / Author Alerts) for new citations or new papers by selected authors.

Visual tools

LitMaps

  • is a so-called freemium application, offering a stripped-down free version in addition to a paid version. 
  • Searches can be performed without logging in, but all features of the free version are only available by creating a user account.
  • LitMaps utilizes citation networks to find publications linked in various ways and presents search results interactively and visually.

How to Use

Enter a seed paper into the search, for example: the author, DOI, Pubmed ID, or arXiv ID of a relevant publication you have previously found. You can also search for a seed paper using keywords.

  • Explore Related Articles.

Search results page:

  • Recommendations for relevant sources and a visual representation (literature map, Litmap) showing how the recommended sources are connected.
  • Adjust your search recommendations with the Explore function > More like this / Ignore for now / Never recommend this.
  • Adjust search recommendations using the search algorithm, selecting either Top Shared Citations & References (get publications connected to your literature map through citations); Common Authorship Patterns (get publications from the same/similar authors); Similar Abstract & Title Content (get publications with similar content to those in your literature map).
  • Export articles: save search results in RIS, BibTeX (.bib), or CSV format.

When logged in:

  • Monitor: enable email notifications when new relevant articles are published.
  • Design: create your own mind-map from the sources you find.

Research Rabbit

  • is a free application that requires creating a user account.
  • ResearchRabbit recommends publications to users based on bibliographies, citation chains, and text similarity, presenting search results interactively and visually. 
  • The application relies on the citation databases of SemanticScholar and PubMed.

How to Use

Create a collection and add one or more seed papers to it by entering the article’s title, DOI, PMID, or keywords into the search. You can also upload references as a .RIS or BibTeX file.

Search Results Page:

  • You can proceed by choosing whether the application shows you recommended similar articles (“Similar Work”), previously published articles (“Earlier Work”), or articles published after the seed paper (“Later Work”). 
  • You can also explore the seed paper’s bibliography (All References), publications citing the seed paper (All Citations), or other publications by the same authors (These Authors).
  • The application shows you networks between articles and authors, allowing you to navigate through the network to discover new, interesting articles.
  • ResearchRabbit works best with slightly older publications, as citation and other networks have had time to develop.
  • You can add relevant sources to your collection for safekeeping and continue refining your search based on them.
  • You can save search results in formats such as .RIS, which is compatible with Zotero.