Category Archives: About Resources

What are Search Hedges?

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A “search hedge” is a library term that describes one of two things:

  • Filter: A pre-set feature found in some literature databases, that enables the user to be guided through a process to locate articles on a specific type of question.
  • Hedge: A published (and sometimes validated) comprehensive search strategy for a database on a specific concept or topic, that can be added to a search, customized, or used as a complete ready-made search.

Search Filters

Search filters are found within a database and work by assisting the user with locating articles for a specific type of question by filling out a form/selecting a pre-set filter.

PubMed Clinical Queries

PubMed Clinical Queries are a built-in search hedge found in PubMed, that assists users in locating clinical studies to answer clinical questions. Users simply enter their search terms and answer several questions (such as whether the question is related to diagnosis, therapy, prognosis, or etiology), and from there PubMed adds a pre-set hedge that is designed specifically for the answers provided.

The search hedge itself is “hidden” from the search strategy seen by the user, however the complete hedge can be viewed in the Clinical Queries filter details.

Embase Search tools

When using Embase (on the Elsevier platform) there are several built-in search tools available to help quickly filter results when searching on specific topics, including: PICO, PV Wizard, and Medical Device.

PICO

The PICO search tool assists in doing evidence-based practice by providing separate sections to enter each component of the PICO framework (population, intervention, comparison, outcome) as well as study design, to quickly identify clinical studies to answer the clinical question being addressed.

PV Wizard

The PV Wizard (PV stands for pharmacovigilance) allows the user to locate articles that address drug monitoring and adverse events using specific drug names (including trade, generic, and alternate names), with buttons to limit to things like adverse reactions, drug interactions, drug combinations, as well as special situations (pregnancy, breastfeeding, pediatric, geriatric, organ failure, etc.).

Medical Device

The Medical Device search allows users to quickly locate clinical and pre-clinical studies on general and medical devices, including manufacturers information and adverse events. This search hedge was developed and validated by industry representatives to ensure that it aligns with best practices for medical device monitoring.

Embase Quick Limits

Embase has several “quick limits” which are essentially search filters that can be added using a single click. These limits can be added by either checking off a box or by adding a specific field code to your search strategy.

  • Humans: Either the Humans quick limit button or the field code [humans]/lim
  • Animals: Either the Animal quick limit button or the field code [animals]/lim
  • EBM: Quick limit button for Cochrane Reviews, Controlled Trials and RCTs

Search Hedges

Search hedges are comprehensive search strategies for a specific database on topics or concepts that have been devised by librarians or information professionals. These hedges are published and available for anyone to use, and many are also validated. While hedges can be used on their own, as ready-made searches on various topics, they are most often added on to the user’s search strategy to limit or narrow the results.

Most search hedges are designed for things like specific populations, study types, diseases or conditions, or outcome measures. Typically a search hedge can simply be copied and pasted into the database, and then using the Boolean operator AND, added to a search already created.

Embase Study Type Hedges

The Embase Study Type Hedges are standardized search strategies for common and frequently used concepts that can used along with a search query. These search strategy hedges can be copied and pasted into the search box in Embase and then added to an already designed search using the Boolean operator AND.

These hedges are to be used to focus on locating specific types of clinical or experimental studies, and each hedge has an option for either sensitivity (comprehensive) and specificity (focused) based results.

There are several types of hedges available on Embase.com.

  • General Study Types: Therapy, Diagnosis, Prognosis, Etiology, Economics, etc
  • Hedges by Topic: Diabetes, Real-World Data, Cost Effectiveness, DEI
  • Animal Breed Hedges: Species-specific hedges for most animals used in research and agriculture

Locating Search Hedges

Since search hedges are published search strategies on specific topics, they can be found in a variety of places online. Some, such as the Study Type Hedges in Embase and the Study Type Filters in PubMed, are available from the database itself. Others can be found on various library websites, published literature, and in special search hedge repositories (though these may not be validated).

It’s common to find search hedges in systematic review resources, since systematic reviews require comprehensive search strategies, and search hedges can provide just that.

A validated search hedge is the “gold-standard” and has been independently tested and verified, so if there is a validated hedge available for the topic you are looking for, that is your best option.

Search Hedge Sources

Suggested Reading

What is the difference between a filter and a hedge?. J Eur Assoc Health Info Libr [Internet]. 2016 Apr. 1 [cited 2025 May 6];12(1). Available from: https://ojs.eahil.eu/JEAHIL/article/view/95

MSK Chatbots Can’t Perform a Literature Search

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MSK now offers employees access to Open WebUI, a source for several chatbots available for workplace use. But if you think this tool can be used for searching the literature, think again.

What is Open WebUI and How Do I Access It?

This portal is “a proprietary, user-friendly, and PHI-secure portal where staff can access a wide array of popular large language models (LLMs) as well as tools for experienced developers behind the MSK firewall.”

To access:

  1. Log on to the VPN or be onsite
  2. Visit https://chat.aicopilot.aws.mskcc.org/
  3. Select “Continue with MSK PingID” if prompted
  4. You’ll then get the message “Account Activation Pending” followed by “Contact Admin for WebUI Access.”

No further action is needed and contacting admin isn’t necessary. You will not get confirmation once your account has been activated. But once it has, visiting the URL while onsite or on the VPN will take you to the tools.

Open WebUI includes the following chatbots:

Chatbot Description
Amazon Nova Pro A reasoning model for general analysis and summarization. Knowledge cutoff date: Unknown
Claude Sonnet 3.5 A general-use model by Anthropic. Effective with code generation. Knowledge cutoff date: April 15th, 2024
Claude Sonnet 3.7 Improved version of Sonnet 3.5, and also targets code generation as a differentiator. Knowledge cutoff date: October 2024
Claude Sonnet 4 High intelligence and balanced performance. Good for complex coding/debugging, detailed explanations, and documentation review. Detailed prompts recommended. Knowledge cutoff date: January 2024
DeepSeek R1 A reasoning model for logical inference, math problem-solving, code generation, or text-based clinical reasoning. Cannot process images. Knowledge cutoff date: October 2023
OpenAI o1 A reasoning model that thinks before it answers, making it suitable for deep analysis, task breakdown, or image-based clinical analysis. Knowledge cutoff date: October 2023
OpenAI GPT-4o A general-purpose model that balances quality, speed, and cost-effectiveness. Knowledge cutoff date: October 2023

You can toggle between tools on the top left of the page and click the “set as default” option under a tool name after you’ve selected it.

Why Can’t I Use These Tools to Perform a Literature Search?

When you ask Amazon Nova Pro to perform a literature search, it appears to do so:

A screenshot of Amazon Nova Pro appearing to summarize the literature in response to a prompt.

However, a follow-up question reveals that all is not as it seems, and that any citations provided are likely not real:

Amazon Nova Pro answering a prompt asking if it searched databases to come up with its answer. It says it did not.

Other tools are clearer about their limitations from the start:

OpenAI o1 saying it does not have database access and giving advice on how to search.
Claude Sonnet 3.7 saying it does not have database access and recommending speaking to a librarian.

What Should I Do Instead?

There are AI tools that specialize in searching the literature, but even these are typically limited to open-source texts. Use these tools cautiously, perhaps in the brainstorming and planning stages of a project.

As an alternative, we welcome you to contact us to request a literature search.

Want to learn more about the use of AI for literature searching? Sign up for our next class on August 19 from 12-1 pm.

From a PubMed Record to NCBI’s Gene information Portal

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PubMed – the National Library of Medicine’s database of biomedical literature that will celebrate its 30th anniversary in January 2026 – is an incredible resource that’s freely available to all.

So much so in fact that many other search tools, including Google Scholar and most of the generative AI research assistants that are popping up at a dizzying speed, heavily rely on PubMed for their content needs, especially since the National Center for Biotechnology Information (NCBI) has always been eager to build APIs and other tools to help facilitate collaborative relationships with developers of other research tools.

One of the downsides, however, of discovering PubMed’s content solely via other search engines and tools is that users miss out on some of the incredible value-added links to other information that appear within each PubMed record. This is particularly true for searches on topics with a genetic information or bioinformatics aspect.

Take this example (inspired by NLM training exercises):

You are interested in exploring how the CYP2r1 gene might impact vitamin D deficiency risk.

A basic search in PubMed might look something like this:

Clicking on the Title to view the Full Abstract view, users can scroll below the abstract text to see the MeSH terms and other Related Information – see:

The Related Information links include a link to NCBI’s Gene information portal which:

“integrates information from a wide range of species. A record may include nomenclature, Reference Sequences (RefSeqs), maps, pathways, variations, phenotypes, and links to genome-, phenotype-, and locus-specific resources worldwide.”

The Gene record can also include GeneRIFs or a “Gene Reference into Function”.
See https://www.ncbi.nlm.nih.gov/gene/about-generif for a more detailed description.

“GeneRIF provides a simple mechanism to allow scientists to add to the functional annotation of genes described in Gene.”

As per https://www.ncbi.nlm.nih.gov/books/NBK3841/#EntrezGene.Bibliography:

“A GeneRIF is a concise phrase describing a function or functions of a gene, with the PubMed citation supporting that assertion.”

Filtering out the references that address a specific gene’s function can be a useful time-saver when literature searching.

For those who find the Gene records a bit overwhelming and prefer to stay within the familiar PubMed environment, limiting PubMed search results to those items that have been added as Gene RIFs can be filtered out in a PubMed search by adding “pubmed gene rif” [Filter].

For example, adding it to the PubMed search string:

“CYP2R1 gene” AND “vitamin D” AND “pubmed gene rif” [Filter]

If you have any questions or want additional guidance on designing specialized literature searches, feel free to Ask Us at the MSK Library.