What’s NOT: More About the Boolean Operator “NOT”

Boolean Operators (AND, OR, NOT) are tools for combining search terms and are inherent part of online database searching. While experienced searchers will use Boolean Operators directly in their search strategies, even novice searchers that just enter a string of terms into a database’s search box will end up indirectly using the Boolean operator AND, as each space between words will be treated by the database as AND, thus combining each term together into a search strategy that would retrieve results that have all terms present.

Image Source: https://sru.libguides.com/english/librarybasics/booleanoperators

Most search strategies will either use just AND or a combination of both AND and OR. The third Boolean operator, NOT, is much more complicated and requires some understanding to use properly in a search.

Using the Boolean Operator NOT

The Boolean operator NOT can be used when a term or terms needs to be excluded from your search strategy.

For example, if you were interested in articles that looked at children with cancer, but you did not want articles that looked specifically at infants, you could create a search strategy like this:

cancer AND child* NOT infant*
— or —
(cancer AND child*) NOT infant*

The Problem with NOT

When using the Boolean operator NOT to exclude terms, it can become problematic when the database excludes records that contain both the term(s) you want to exclude and the term(s) you want in your search.

In the above example, not only articles about cancer in infants will be excluded from the results but it will also exclude any articles about cancer in both children and infants.

Information professionals (librarians and informationists) advise using the Boolean operator NOT with extreme caution when conducting searches. It’s better to reach out to an information professional for assistance with complex search techniques and how to best proceed with a search when there is a term you want to avoid.

Variations Across Databases

Not all databases function the same way, and using the Boolean operator NOT is no different. While most databases allow for using simply NOT to exclude terms, depending on the database or platform, you might need to use the operator AND NOT instead (Scopus), or once the search is performed use the Exclude button found within the Refine Search panel (also in Scopus).

Takeaway

The Boolean operator NOT should be used with extreme caution. It is best to consult a Librarian on its use in your search.

Papermill Detection Software

It is not at all surprising in this era of “fake” everything, that there would suddenly be a business need for “fake paper” detection tools. Along with “plagiarism detection” and “image duplication or image manipulation detection”, another potential risk to the integrity of the scientific record that many publishers are now proactively on the lookout for during the manuscript submission process is “papermill detection”.  

According to this COPE blog post on “Potential paper mills“:

“This term describes the process by which manufactured manuscripts are submitted to a journal for a fee on behalf of researchers with the purpose of providing an easy publication for them, or to offer authorship for sale. The concerns with these submissions include faked or manipulated data/images, the use of stock images, substantial authorship changes, and plagiarism, which is not detected because it comes from a translated version of another article.” 

Publishers are already starting to incorporate these tools into their workflows. For example, a year ago, in April 2023, the STM Scientific Integrity hub (that provides tools/services for publishers in a cloud-based environment) launched their papermill detection tool as a:

“stand-alone application that allows publishers to automatically screen uploaded papers against key indicators that suggest that the manuscript has or may have originated from a paper mill”.

This year, in March 2024, Wiley announced that its journals will soon be piloting an “AI-powered Papermill Detection Service” integrated in their manuscript submission system.

Tools like “Papermill Alarm” have been reported on in the literature as far back as 2022:

Else H. ‘Papermill alarm’ software flags potentially fake papers. Nature. 2022 Sep 23. doi: 10.1038/d41586-022-02997-x. Epub ahead of print. PMID: 36151206. https://www.nature.com/articles/d41586-022-02997-x

Although this type of detection is not something that individual authors would need to use pre-emptively, other tools  – like iThenticate, a plagiarism detection tool – are now being subscribed to and made available to all potential authors in the MSK community via the MSK Library.

Questions? Be sure to Ask Us at the MSK Library!

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