Adam Day

There’s this phrase used by some technologists: ‘epistemic security’. Epistemic security has to do with things like the spreading of misinformation on social media. I.e. if we spend enough time on social media reading unreliable information, how does that influence us? That’s a matter of epistemic security. Epistemic security is interesting because if you start a conversation about epistemic security at a party, they don’t invite you back.

The Papermill Alarm

I remember finding ChatGPT usage in a research paper for the first time. It was April 2023, and a Twitter user pointed out that you could identify bots by their use of the phrase “as an AI language model…”. It’s a hallmark of ChatGPT usage. So I searched Google Scholar for the phrase  … and found just one paper.

Detecting genAI: beside the point?

TL;DR: The current version of the Papermill Alarm detects signals in 98.9% of the Hindawi retractions conducted over the last 12 months.** It’s never nice to see the harms caused by papermills, but it is good to see independent verification of the Papermill Alarm’s predictions.

Here’s a question: Why are there 2 multi-squillion-euro detectors at CERN’s Large Hadron Collider?

Predicting retractions with the Papermill Alarm

It’s 1 January 2021. Dozing in bed, floating in that warm &amp; fuzzy limbo between dreams and reality, and that’s where it hits him. That lightbulb moment. (At last!) He sits bolt-upright in bed, punches the air and shouts: “You know what, honey, I’m gonna start a papermill!”. She snorts awake; reluctantly conscious. Oh no. Not again.

 Not another hare-brained scheme…

“…and, by the end of next year, we’ll publish 20,000 fake papers!”.

Impossible to ignore

TL;DR: We can detect individuals with a high probability of being involved in milling papers. The question is: how should we respond?  A few years ago, my bike was stolen. It was an organised job. The thieves arrived after dark, cut a hefty lock clean off, and my bike disappeared silently forever. I imagined it dismantled and sold off into some vast black market network. Poor bike. The police admitted that they weren’t going to do anything.

Keystone: papermill detection with network analysis

TL;DR: the rate of Papermill Alarm alerts is significantly higher in gold OA content than it is in subscription content. If you’re concerned about papermills, Clear Skies offers the Papermill Alarm: the world’s leading papermill detection tool. Get in touch for a demo. I’m a big believer in Open Science.

Papermills prefer Open Access

TL;DR: peer-review times appear to have been growing for a long time. The effects of COVID-lockdowns on peer-review are surprising.

A few months ago, I was invited to referee a research paper. So, I guess the editor thought that I was one of the 2 best people in the entire world to review this thing. That’s how it works, right? Flattered, I flagged the editor’s email to signal its importance and I got straight to work!

Is science getting slower?

This is

TL;DR: Join me at ConTech Live to hear about a recent project with Open Credo to see if we could detect unusual co-authorships in a dataset created by Anna Abalkina. Sign up here! Papermilling has a few definitions which you see here and there.

(The?) 3 kinds of papermills

TL;DR: There’s been a recent major upgrade to the private Papermill Alarm. It looks like we can predict the inclusion of journals on the Chinese Academy of Sciences (CAS) lists. You know how data scientists make predictions?

Cast a wide net

There’s a quote attributed to Ernest Rutherford: “That which is not measurable is not science. That which is not physics is stamp collecting”. I think his point was that a lot of scientific work is just

 documenting

things. In Rutherford’s day, there was a lot of exciting new

 creative

work happening in physics, so perhaps physics seemed special to him.

We need a chat about ChatGPT

Recently, I gave a presentation on the APIs for Papermill Detection offered by Clear Skies Ltd. I also touch on a newer service called the Clear Skies Standard Report. More on that in future posts… :)  Here’s the video:  https://medium.com/media/ee5a04aaed9fc53d2748e64516178ebe/href Would you like to know more?

Video: APIs for Papermill detection (ConTech API Series)

The first time I flew over the North Atlantic was quite an experience. Through the clouds, I could see some little white boats out sailing in the sea. It was puzzling: from 30,000 feet, those boats must have been huge for me to be able to see them at all.

How to find all the papermills (step 1)

This post is about The Papermill Alarm: an API for detecting potential papermill-products. There’s a field of study called ‘stylometry’ where we look at the statistical properties of someone’s writing and use that to model their ‘style’. People write in idiosyncratic ways.

The Papermill Alarm: Patterns in PubMed

The Papermill Alarm draws a line between papers which have the characteristics of papermill-products and those that don’t. Given data like that shown below, where red dots represent papermill-products and green dots represent normal papers, where should we draw that line?

Where to draw the line? Precision and recall

So, we’ve established that papermills like to use templates. We see templates in referee reports and in the text of cookie-cutter research papers. There’s an important insight here: Templates are used in legit academic behaviour as well as in industrial research fraud. So we need to be careful — we can’t assume that templates are necessarily a sign of research fraud.

Thank you for your warm work… earnestly

Last week, a paper I wrote on the subject of peer-review fraud was published in the journal

 Scientometrics

(free link here, preprint here)

 .

It was an interesting project to work on. I found a lot of examples where one referee would write a report during peer-review and then another referee would write an identical report in some other peer-review of some other paper.

Papermills in peer-review

Also… what is an API?

The Papermill Alarm API, is a service which you can send some article metadata to and which will return an alert telling you if the paper

 looks like

past papermill-products. Anyone can use it, but it definitely helps to have the support of an IT or data professional.

How to use the Papermill Alarm API

I once saw a brilliant presentation about how simple data analysis can detect credit card fraud**. The presentation showed a

 pattern

in how people use their credit cards. Given a large number of people who had been victims of credit card fraud, this pattern showed there was just 1 store in-particular where they had all used their cards. There was no

 observational evidence

of someone at that store stealing card details.

Patterns and Evidence (and how to find papermills before peer-review)

This is Ralph. How tall is Ralph? It seems simple, you could just hold a ruler up to the screen. But when you look at the ruler and use it to measure Ralph, are you actually measuring

 Ralph

, or are you measuring the ruler and using that as a

 proxy

? How accurate is your measurement? Are you including fur in the measurement? What if Ralph were to stand on his hind legs, like a mighty bear — how tall would he be then?

The definition of plagiarism

Stories by Adam Day on Medium

The first time I flew over the North Atlantic was quite an experience.
Through the clouds, I could see some little white boats out sailing in
the sea. It was puzzling: from 30,000 feet, those boats must have been
huge for me to be able to see them at all. Suddenly, the clouds were
gone and, through clear skies, I could see a really big 'little white
boat' and I understood at once what I had been looking at.

<figure>
<img
src="https://cdn-images-1.medium.com/max/1024/1*DePhN8tzJjWHH38gUksYLA.jpeg" />
<figcaption>Image CC-BY: wiki commons <a
href="https://commons.wikimedia.org/wiki/File:Sarqarput-strait-iceberg-aerial.jpg">https://commons.wikimedia.org/wiki/File:Sarqarput-strait-iceberg-aerial.jpg</a></figcaption>
</figure>

With papermills, people often say that they only see 'the tip of the
iceberg'. (It's almost a cliché!) If fake papers were easy to detect,
then forgers would just learn to get better at writing them. I guess
that's what actually happened over time and it's why we need to be
super-careful about sharing detection methods.

This is why I've thought very carefully about making this post (and why
I've no intention of publishing steps 2, 3 etc).

#### Here's what we know:

- [Papermills use duplicate submission
 routinely](https://medium.com/p/21ebd625ad40)
- [Detecting duplicate submission
 is easy](https://youtu.be/6yA3phww3m8?t=1579)
- [Retrospective analysis is a
 necessity](https://medium.com/p/9ab21e84d0c9)

With this in mind, it's actually very simple for publishers to see
the iceberg.

1. Make your submission dates visible in Crossref.

It might not be trivial to do, but it shouldn't be hard or
controversial. Most journals make their submission dates visible in
article XML, so this wouldn't make any data visible that isn't already,
it just makes it easier to work with. In fact, several publishers are
doing this already.

2\. Search for your submissions in Crossref.

This is also not hard to do. The results will show you when your
submissions were published by others and (with the above step having
been done) when they were submitted to those other publishers.
Conveniently, there are some pre-built options that will make doing this
trivial (see 'Article Tracking Options' below!).

3\. Finally, if you find a duplicate submission, contact the publisher
of that duplicate submission and show them: the submission and decision
dates as well as the full-text. For them to confirm duplicate submission
requires only a quick manual comparison of the manuscripts. It's much,
**much** quicker than a full misconduct investigation.

### What does this give us?

Well, there are 2 things:

- All of the papermill submissions (at least all of those that have been
 using duplicate submission --- there are exceptions).
- Any other authors using duplicate submission as a hedge.

Isn't this great? No fancy AI, no need to actually detect and prove the
fakery. Here is all the evidence you need to prove a paper has breached
your terms of service. Furthermore, if we take this to its logical
conclusion(which might be an up-front cross-publisher full-text check
made at the submission of any article), you can see that there really
isn't any way around it. The paper-mills will have to stop sending the
same paper to different publishers concurrently. That will slow them
down considerably. It's also why I'm comfortable sharing this publicly.

But how to tell the two apart --- papermills and 'other' duplicates?
Well, I'm not going to share that here, but what I will say is that it
isn't hard. The iceberg is obvious once you see it through clear
skies ;)

At this point, it's up to you how you proceed. You might want to analyse
the data to learn more about papermills. You might want to conduct
misconduct investigations. You might see opportunities to collaborate
with other publishers. After all, this method does require that we all
work together.

### Article tracking options

1. The SAGE Rejected article tracker.

This was a project that started out as [a blog post that I wrote some
years ago in my spare
time](https://publisherad.medium.com/rejected-article-tracking-with-the-crossref-api-22d75a874904).
It later became [an open source project from SAGE Publishing with its
own peer-reviewed
paper](https://joss.theoj.org/papers/10.21105/joss.03348). It's free and
it will get the job done (if a little slowly). Note that, in this case,
it's important to track all articles, this includes accepted articles,
new submissions and (importantly!) abandoned submissions as well as
rejected articles. Remember how [I said that we sometimes see the same
paper published in 2 places](https://medium.com/p/9ab21e84d0c9)? This is
how to find those cases.

2\. [My own "Article
Tracker" API](https://rapidapi.com/clear-skies-clear-skies-default/api/article-tracker/details).

This is part of a side-project (not related to my work at SAGE) and I
hadn't intended to make it publicly available, but after seeing the
value of this tool in detecting papermills, here it is. It's the best
tool of its kind as far as I know. I hope that it helps with
this problem.

The Article Tracker has the following features:

- Fast: in testing, I've been able to track around 500 articles
 per minute.
- Accurate: the current accuracy is around 96--98% on test data. There
 is a planned upgrade which will push accuracy even higher.
- Does duplicate submission checking (as described above) out of
 the box.
- I've set pricing at a low level where I think any publishing house
 should be able to easily afford to search for all of their submissions
 as well as historic submissions without running into limits.

This blog post is actually the first time I've advertised the Article
Tracker's existence, so you might consider this to be a soft-launch of
the service. Any questions, comments or feedback would be very welcome.

- [You can contact me through the Article Tracker's parent
 company](https://clear-skies.co.uk/contact/) or
- [find me on Twitter](https://twitter.com/AdamSci12).

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