What Difference Does It Make?

A few days ago, Retraction Watch published the top ten most-cited retracted papers. I saw this post with a bar chart to visualise these citations. It didn’t quite capture what the effect (if any) a retraction has on citations. I thought I’d quickly plot this out for the number one article on the list. The plot […]

White label: the growth of bioRxiv

bioRxiv, the preprint server for biology, recently turned 2 years old. This seems a good point to take a look at how bioRxiv has developed over this time and to discuss any concerns sceptical people may have about using the service. Firstly, thanks to Richard Sever (@cshperspectives) for posting the data below. The first plot shows the number of […]

The Great Curve: Citation distributions

This post follows on from a previous post on citation distributions and the wrongness of Impact Factor. Stephen Curry had previously made the call that journals should “show us the data” that underlie the much-maligned Journal Impact Factor (JIF). However, this call made me wonder what “showing us the data” would look like and how journals might […]

Wrong Number: A closer look at Impact Factors

This is a long post about Journal Impact Factors. Thanks to Stephen Curry for encouraging me to post this. tl;dr — I really liked this recent tweet from Stat Fact It’s a great illustration of why reporting means for skewed distributions is a bad idea. And this brings us quickly to Thomson-Reuters’ Journal Impact Factor […]

Waiting to Happen: Publication lag times in Cell Biology Journals

My interest in publication lag times continues. Previous posts have looked at how long it takes my lab to publish our work, how often trainees publish and I also looked at very long lag times at Oncogene. I recently read a blog post on automated calculation of publication lag times for Bioinformatics journals. I thought it would […]