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Data Diversity Podcast #3 – Dr Nick H. Wise (3/4)

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Welcome back to the penultimate post featuring Dr Nick H. Wise, Research Associate in Architectural Fluid Mechanics at the Department of Engineering, University of Cambridge. If you have been with us for the previous two posts, you would know that besides being a scientist and an engineer, Nick has made his name as a scientific sleuth who, based on an article on the blog Retraction Watch which was written in 2022, is responsible for more than 850 retractions, leading Times Higher Education to dub him as a research fraudbuster. Since then, through his X account @Nickwizzo, he has continued his investigations, tracking cases of fraud and in some cases, naming and shaming the charlatans. In this four-part series, we will learn from Nick about some of the shady activities that taint the scientific publishing industry today.

In part three, we learn from Nick about how researchers try to generate more citations from a single piece of research through a trick called ‘salami slicing’ and the blurred lines between illegality and desperately coping to meet with the unrealistic expectations of academia (to the point of engaging with fraud). Below are some excerpts from the conversation, which can be listened to in full here. 

Citation count was once a proxy for quality and now it is citation count regardless of quality. People are only looking at the citation count, and not the actual quality. Actually assessing quality takes a lot more effort. 

‘Salami slicing’ and the Game of Citations

LO: What do you think is better for science? A slower, more thoughtful process of publishing and everything in between? Or more information, more research, but then things like fraud slip through and occur more frequently?

NW: I don’t think there’s necessarily more research. Another phenomenon that paper mills take advantage of is salami slicing. Imagine you have completed a research project. Now you could write this up as one, thirty-page paper or two, twenty-page papers. You could write two comprehensive papers or try to put out multiple ten-page papers where you have some minor parameters changed. I see this happening in nanofluids research because it is an area of research close to mine. The nanofluid is simply a base liquid – it might be water, it might be ethanol – and into that you mix these very small nanoscale particles of some other material, such as gold, silver, or iron oxide. And in this sort of mixture of liquid and particles, you want to investigate its fluid flow and describe this with some differential equations. You can use computers to solve the differential equations and then plot some results about velocity profiles and heat transfer coefficients, etcetera. Now, you could write a paper for a given situation where you say, I’m not going to specify the liquid, but here is a general and viscosity of this liquid. If you want to apply this to your own research, you plug in the density and viscosity of your liquid, and likewise the particles. I’m not going to specify which particles are used, because all that changes is their density and their heat transfer coefficient properties. So that’s one way you could do it.

Another way to do it is to go I’m going to write a paper about water and gold particles; that’s one paper. Then you can write another paper which has water and silver particles, and then you can write one with ethanol and iron oxide, and there are so many varieties. You can also vary the geometry that this flow is going around, and you can add in an electric field and a magnetic field, etcetera. You can build up in this n-factorial way. There are thirty possible liquids multiplied by a hundred possible particles and multiplied by however many geometric configurations. You can see that this is what they are doing. Rather than writing a few quite general comprehensive papers, they are writing hundreds of very specific papers which enables them to produce more papers and sell more authorships and put more citations in. But this overwhelm of papers produced; there’s still only so many peer reviewers, and so many editors. And this phenomenon happens in lots of fields, they find something where there are just these variables that they can keep writing almost the same paper. Yet, the paper is original. It has not been done before. It is incredibly derivative, but that is not necessarily a barrier to publication.

LO: What I’m getting from this is, this is part of the whole system, and the issue at hand is definitely enabled by certain motivations like getting more citations. You can take one big piece of salami or publish that in one book, or you can slice the salami thirty ways. And if they are in the position to slice the salami, they say why not, I suppose, right? A game is there to be played.

NW: Right, they are playing the game that is in front of them. And again, there are people who do this who are not from a paper mill. They just want to maximize the number of citations and publications. The question is why are they doing this? Why do they want to maximize their publications? Because they want a promotion, or they want a tenured job. There are also countries where you get a cash reward for publishing a paper in a good journal so the more papers you publish, the more money you get paid. Your government might have told all the universities that they need to increase their ranking in the World University rankings. How do you do that? By increasing your research output and the citations you get. That is another driver. These drivers come from all sorts of places but there is always an emphasis on numbers. Citation count was once a proxy for quality and now it is citation count regardless of quality. People are only looking at the citation count and not the actual quality. Assessing quality takes a lot more effort.

LO: Citations used to be a proxy for quality, but that is not the case anymore. But it still implies the quality of the research, or you would hope.

NW: You would hope, but only because there is an assumption that the only reason something has a lot of citations is because it is good quality. Citations are also easier to count. Quality is much harder to account for, but that incentivizes people to do things like cite their colleagues. Again, you could still track it if people from the same university were citing each other. But then you get bigger scale things with middlemen who organize people from across the world to cite each other or just do it for cash. If you are publishing and you are producing papers to order, each one of those papers has a reference section which is real estate. You can throw in and have some genuine references which are relevant to this paper, but you can also throw in some irrelevant references that someone paid you to include. You can also pay someone to include references that are actually relevant to a topic.

LO: If it is relevant to a topic, it is almost like merely encouraging someone to be aware of certain work as opposed to a scam, which sounds like a gray area.

NW: Well, I would say that as soon as someone is paying money, then it starts to be illegitimate. But I mean if someone emails you and says “I’ve just published this paper, I think you might be interested, it’s in your research field: maybe read it or maybe you do cite it”, it’s different from someone emailing you to say “I’ll pay you £50 if you cite my paper” and you do. Then I would say that you have crossed a line. So, it does get very gray. Then there are these organized paper mills who are doing this as a business and that is where I think it becomes quite clear that it is probably not legitimate.

Facebook (authorship) marketplace

NW: You could go on Facebook and there are people selling authorship of their paper as a one off. There are PhD students in some country with no research funding who say “it costs $2500 for the article processing charge for me to publish where I would like to publish, I do not have $2500 so if you pay the $2500, you can be first author on the paper” and that is the only way they can get their paper published. They’re not doing this as a business, they’re just doing this once for this one paper. And you get people responding. Quite often professors or more established academics with access to budgets are the ones who will say yes. And the only thing that the person has done is to provide the funding for the publication.

The minimum thing that one is supposed to have done to be considered an author is to have either written the draft or reviewed and edited the paper. You might have also done data analysis or conceptualization. I think we would agree that if all this person does is just pay the fee for publication, then that is not acceptable. But what if they read the paper and then made a couple of comments? Now they have reviewed and edited it, and so now they have done review, editing and funding. There are many big labs around the world that have some very senior scientist whose name is on every single paper that comes out of the lab. And what have they done? Well, they provided all the funding, and they have reviewed the paper. I bet there are some who have barely glanced at the paper. But let’s say that they have reviewed the paper, and they provided the funding for the publication. Is that what makes it different to the person on Facebook who has found some random professor from another country to pay for their publication? Where is the difference? I don’t think it is an easy line to draw. In this way, the move to Open Access publishing requiring large fees for publication has also driven quite a bit of this phenomenon.

LO: It also seems like you have developed a bit of empathy. Maybe you’ve looked at so many cases and you see that it’s not always clear.

NW: Absolutely. Again, if you have the people running a paper mill, or if you have some professor who is being bribed and waving through dozens of papers, I don’t have much empathy for them. But the Masters or PhD student who has been told that they have to publish papers to get their PhD or even a Masters and they have this demand placed on them, or they even have produced a paper but they need this on the all this money to get it published, I don’t blame them for what they’re doing. It’s the situation they’ve been placed in. It is the system that they are part of. I have a lot of empathy for them.

Look out for the final post coming next week, where we get Nick’s take on what he thinks should be the repercussions for engaging in fraud, and we get a parting tip from Nick on what researchers should do when performing a literature search on papers in their field.

Data Diversity Podcast #3 – Dr Nick H. Wise (2/4)

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We are back again with our second blog post featuring Dr Nick H. Wise, Research Associate in Architectural Fluid Mechanics at the Department of Engineering, University of Cambridge. As is the theme of the Data Diversity podcast, we spoke to Nick about his experience as a researcher, but this is a special edition of the podcast. Besides being a scientist and an engineer, Nick has made his name as a scientific sleuth who, based on an article on the blog Retraction Watch which was written in 2022, is responsible for more than 850 retractions, leading Times Higher Education to dub him as a research fraudbuster. Since then, through his X account @Nickwizzo, he has continued his investigations, tracking cases of fraud and in some cases, naming and shaming the charlatans.

In this four-part series, we will learn from Nick about some of the shady activities that taint the scientific publishing industry today. In this second part, we get Nick’s take on the peer review process and fake research data, and I ask his opinion on where the fault lies in the publication of fraudulent research. Below are some excerpts from the conversation, which can be listened to in full here. 

There are indices like Scopus or Web of Science or SCI, all these different bodies who claim journals are trustworthy, but every journal is going to get attacked by fraud and some will slip through. It is what you do afterwards that matters. 

On the peer review process

LO: As an Early Career Researcher, scientist, engineer, and researcher yourself, is your trust in the whole system still intact? Do you still see value in the peer review process? 

NW: It has absolutely changed how I read a paper and how I view particular journals. When you see a problem happening in a journal that you have read in your research or a journal you have considered submitting to, it really gives you pause for thought. There is an entire ecosystem of journals, right from the from the very good down to the very bad, that are implicated. There are indices like Scopus or Web of Science or SCI, all these different bodies who claim journals are trustworthy, but every journal is going to get attacked by fraud and some will slip through. It is what you do afterwards that matters. Another phenomenon that particularly happens with publishers with a wide list of journals, is that the paper mill will legitimately buy the journal. They may even take it over in a hostile way: they will make a clone of the journal and the website, and they will even redirect the publisher’s link to a different website. They now control a journal that is officially on this trustworthy list. Now they have a short period of time before someone notices and in that time, they will try to publish as many papers as possible and charge everyone for publication. They will absolutely cram this journal with any content. It does not even have to be relevant to the topic because they’re fully in control of the whole process up until the publisher notices and removes the journal from the list. For an author who needs a journal in a paper published in a well-regarded journal, they have achieved what they needed but as soon as the journal is removed from the list, then it becomes worthless. But there is a large supply of these journals, and they will keep trying to take them over. This tends to happen with low tier journals, but there are also paper mills which are targeting journals with an impact factor of over five, over ten – the supposedly absolute top tier journals. 

Between incompetence and conspiration

LO: These days, fraud is so convincing, scams are so rampant, and they always target your insecurities, the insecurity here being authors who want citations. 

NW: I would say that it is not a scam or fraud for the researcher, in the normal sense. These people are selling citations, and the buyer gets citations as opposed to someone getting cheated for their money and getting nothing in return. They are scamming the publishers and scamming the scientific community, but they are not scamming an actual person paying the money. It is a business that is operating as it says it is.  

LO: What does it say, though, that fraudulent papers are still getting through the peer review process. It’s still quite a long way from first draft to publication, and we have seen some cases where remnants of text from Chat GPT replies like “as a large language model…” gets through the review process. In your mind, what does it say about the industry? What’s happening here? 

NW: I think that it is somewhere between incompetence, people in a rush, and peer reviewers being bypassed or being paid. They could also be colluding with authors or the paper mill. To be fair, there are dodgy things that get through a legitimate peer review in the first place. All the peer reviewers are independent but how many people read every single word right of a paper they peer review? Not everyone. People have different standards that they hold themselves to. There is no agreed standard of what you are supposed to do to peer review a paper. As I’m sure anyone who has received peer review reports would know, sometimes you receive a five-page PDF document with hundreds of bullet points, and sometimes you receive a paragraph which maybe took them half an hour to put together. Legitimate peer reviewers could just not do a good job. Then there are also people who pride themselves on doing a load of peer reviews, and in fact you can get certificates from the publisher about how many peer reviews you do. There are people who say they peer review nearly a paper a day – I doubt that they are doing a great job at it.  

Even if someone is reading the text, how much is a peer reviewer supposed to be checking the data? Should someone be trying to run statistical analysis to see if they have been fudged? Should they be spotting that the image is manipulated? Is that something we should expect the peer reviewer to be doing? Or should a peer reviewer go into a review assuming the work is honest? It becomes a different process if you are also thinking about whether a piece of work is fraudulent or not. The easiest things to find are the people who are very lazy or very incompetent and there is just something that is so blatant that it is hard to miss. But if most people are trying to cover their tracks, then it comes down to just how well they have managed to do that. Again, if you are including remnants of Chat GPT like “as a large language model” in your text, you are either extremely lazy, or maybe you don’t read English. But if someone got rid of that bit, you would not notice from reading the abstract. You might think this is a bit bland, but people can write bland text; that is allowed. 

Sometimes peer reviewers are definitely compromised, and I don’t know what the balance is. When you see a bad paper, say a paper with an obvious problem or with chat GPT remnants lying around: is that bad peer reviewing or have they been paid not to notice, or even not to do it? I don’t know what the balance is there. I suspect it is more on the bad peer reviewing side than the criminal or the fraudulent to be honest, but I don’t know. There are times when you think OK, well, maybe they were paying the peer reviewers but did the editor look through this? Did the copy editor? We might want to think that copy editors and type setters are going through and questioning these things like this. It really depends on the journal. I have had things come back where they have gone through and changed from a comma to a dash, so they are clearly going through everything character by character. And there are other journals where the typesetter is clearly just taking everything with no thought. Their job is just to transfer what they have been given into the journal paper and they don’t do any spell checking or checking for grammar or anything. But should that be their job? I don’t know. Then there are journals where the only priority appears to be publishing as many papers as quickly as possible. And if you have made that your priority, even if everyone is acting in good faith, you are going to let a lot more things through. If you are just trying to push everything out the door and do things as quickly as possible, you are not going to give the things as much scrutiny. 

Fake research data

Even from doing my own research, I’ve realized that it would be very easy to fake some data. It would be very hard for anyone who wasn’t in the lab to know if data has been faked. There is no real way for someone to check. Even if you go open data; one experiment might need a few gigabytes of video footage to produce one data point. You can say what you have done to produce that data point, but for someone to go and check its validity, they would in theory need access to gigabytes and gigabytes of data that is not shared. But yes, there have been some things where it has been very easy to check. For instance, in material science, there are lots of experiments which result in the spectra diagram, basically producing a squiggly line on a graph. One thing that would always be true, and you don’t need any subject expertise to know this, is that the line should not double back on itself. Every X value should have one Y value. Well, if you are faking this by drawing it by hand with a mouse, it is quite hard to not double back and there are plenty of published Spectra which have bits where a peak bends over. And it is clearly because someone has drawn it by hand, and some of them are very bad. And that is again where you question what is happening with peer review because it is obvious that something is wrong. Sometimes they will even go outside the lines of the bounding box. I do see some of those because they are quite easy to spot. 

Stay tuned as we release the third conversation with Nick next week. In the penultimate post, we learn from Nick about how researchers try to generate more citations from a single piece of research from a trick called ‘salami slicing’ and the blurred lines between illegality and desperately coping to meet with the unrealistic expectations of academia to the point of engaging with fraud.

Data Diversity Podcast #3 – Dr Nick H. Wise (1/4)

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In our third instalment of the Data Diversity Podcast, we are joined by Dr Nick H. Wise, Research Associate in Architectural Fluid Mechanics at the Department of Engineering, University of Cambridge. As is the theme of the podcast, we spoke to Nick about his experience as a researcher, but this is a special edition of the podcast. Besides being a scientist and an engineer, Nick has made his name as a scientific sleuth who, based on an article on the blog Retraction Watch which was written in 2022, is responsible for more than 850 retractions, leading Times Higher Education to dub him as a research fraudbuster. Since then, through his X account @Nickwizzo, he has continued his investigations, tracking cases of fraud and in some cases, naming and shaming the charlatans. Nick was kind to share with us many great insights over a 90-minute conversation, and as such we have decided to release a four part-series dedicated to the topic of research integrity. 

In this four-part series, we will learn from Nick about some of the shady activities that taint the scientific publishing industry today. In part one, we learn how Nick was introduced into the world of publication fraud and how that led him to investigate the industry behind it. Below are some excerpts from the conversation, which can be listened to in full here. 

I have found evidence of a papermill bribing some editors and there have been many, at least tens, if not hundreds, of editors that have been let go or told to stop being editors by journals in the last year because they have been found to be compromised. This could be because of bribery or some other way of being compromised. This is what I try to uncover. – Dr Nick H. Wise

Tortured Phrases and PubPeer: Nick’s beginnings as a Scientific Sleuth  

My background is in fluid dynamics where I mostly think about fluid dynamics within buildings. For instance, I think about the air flows generated by different heating systems and things like pollutant transport such as smells or COVID which can travel with the air and interact with other each other. That was my PhD and the post-doc in the Engineering department.

About three years ago whilst trying to avoid writing my thesis, I saw a tweet from the great Elizabeth Bik, who is possibly the most famous research fraud investigator. She mostly looks at biomedical images and her great skill is she would be able to look through a paper and see photos of Western blots of microscopy slides and see if parts of an image are identical to other parts, or if the image overlaps with images from different papers. She has an incredible memory and ability to spot these images. She’s been doing this for over 10 years and has caused many retractions. I was aware of her work but there was no way for me to assist with that because it is not my area of research. I don’t have an appreciation of what these images should look like.

But about three years ago she shared a preprint written by three computer scientists on her Twitter account about a phenomenon they called ‘tortured phrases’. In doing their research and reading the literature, these computer scientists noticed that there were papers with very weird language in them. What they surmised was that to overcome plagiarism checks by software like Turnitin, people would run text through paraphrasing software. These software were very crude in that they would go word by word. For instance, it would look at a word and replace it with the first synonym it found in a thesaurus. It would do this word for word, which makes the text barely readable. However, it is novel and so it will not flag any plagiarism checking software. Eventually, if you as a publisher have outsourced the plagiarism checks to some software, and neither your editor or peer reviewer reads the text to check if it makes sense, then this will get through peer review process without any problem and the paper would get published.  

For an example of tortured phrases: sometimes there’s not only one way to say something. Particularly if English is not someone’s first language, you don’t want to be too harsh on anyone who’s just chosen a word which just isn’t what a native speaker would pick. But there are some phrases where there’s only one right way to say it. For instance, artificial intelligence is the phrase for the phenomenon you want to talk about, and if instead you use “man-made consciousness”, that’s not the phrase you need to use, particularly if the original text said artificial intelligence brackets AI, and your text says “man-made consciousness” brackets AI. It’s going to be very clear what has happened.  

The three computer scientists highlighted this phenomenon of ‘tortured phrases’, but entirely from within the computer science field. I wondered if a similar phenomenon was happening in my own field in fluid dynamics. Samples of these paraphrasing software are freely available online as little widgets so I took some standard phrases from fluid dynamics, which were the kind that would not make sense if you swapped the words around and generated a few of these tortured phrases, I googled them and up popped hundreds of papers featuring these phrases. That was the beginning for me. 

I started reporting papers with these phrases on a website called PubPeer, which is a website for post-publication peer review. I commented on these papers and started being in conversation with the computer scientists who wrote the paper on ‘tortured phrases’ because they built a tool to scrape the literature and automatically tabulate these papers featuring these phrases. They basically had a dictionary of phrases which they knew would be spat out by the software because some of this paraphrasing software are so crude, such that if you put in “artificial intelligence”, you are always going to get out “man-made consciousness” or a handful of variants. It didn’t come up with a lot of different things. If you could just search for “man-made consciousness” and it brings up many papers, you knew what has been going on. I contributed a lot of new ‘fingerprints’, which is what they call their dictionary that they would search the literature for. That is my origin story. 

On Paper Mills and the Sale of Authorships 

There is also the issue of meta-science, which has nothing to do with the text of the paper or with the data itself, but more to do with how someone may add a load of references through the paper which are not relevant, or they are all references to one person or a colleague. In that way you would be gaming the system to boost profiles, careers, and things like H-index. Because having more publications and more citations is so desirable, there is a market for this. It is easy to find online advertisements for authorship of scientific papers ranging from $100 to over $1000, depending on the impact factor of the journal, and the position of authorship you want: first authorship, seventh authorship, or whether you want to be the corresponding author, these sorts of factors. Likewise, you can buy citations.  

There are also organizations known as paper mills. For example, as an author I might have written the paper and want, or need, to make some money and so I go to this broker and say: I want to sell authorships, I’ll be author number six, but I can sell the first five authorships. Can you put me in touch with someone selling authorships? At the same time, there are people who go to them saying I want to buy an authorship, and they put two and two together acting as a middleman. Also, some of these paper mills do not want to wait for someone to come to them with a paper – they will write papers to order. They have an in-house team of scientific writers who produce papers. This does not necessarily mean that the paper is bad. Depending on where they want the paper to publish, the paper might have to be good if it has to get published. So, they will employ people with degrees, qualified people or PhD students who need to earn some money, and then they will sell the authorships and get the papers published. This is a big business. 

There is a whole industry behind it, and something I have moved onto investigating quite a lot is where these papers are going. When I identify these papers, I try to find out where they are being published, how they’re being published, who is behind them, who is running these paper mills, who is collaborating with them. Something I found out which resulted in an article in Science was that paper mills want to guarantee acceptance as much as they can. If a paper is not accepted, it creates a lot of work for them and it means a longer time before their customers get what they paid for. For example, if a paper that they wrote and sold authorships for gets rejected, they’re going to have to resubmit it to another journal. So something paper mills will do is they will submit a paper to 10 journals at once and publish with whichever journal gave them the easiest time. But still, they want to try and guarantee acceptance and one way to do that is to simply bribe the editor. I have found evidence of a papermill bribing some editors and there have been many, at least tens, if not hundreds, of editors that have been let go or told to stop being editors by journals in the last year because they have been found to be compromised. This could be because of bribery or some other way of being compromised. This is what I try to uncover.

Although I’m not fighting this alone, it can feel like that. Publishers are doing things to some extent and they’re doing things that they can’t tell you about as well. And then there’s other people like me investigating this in their free time or as a side project. Not enough of us are doing it because it is a multi-million-dollar industry that is generating these papers. More papers are being published than ever before so it is a big fight.

Stay tuned as we release the rest of the conversation with Nick over the next month. In the next post, we get Nick’s take on the peer review process and fake research data, and I ask his opinion on where the fault lies in the publication of fraudulent research.