Previously, I took advantage of a dataset that linked preprints to their published counterparts to look at the fraction of papers in a journal that are preprinted. This linkage can be used to answer other interesting questions. Such as: when do authors preprint their papers relative to submission? And does this differ by journal? There’s a bit of preamble. If you just want to know the answer, click here.
On a scientist’s Google Scholar page, there is a list of co-authors in the sidebar. I’ve often wondered how Google determines in what order these co-authors appear. The list of co-authors on a primary author’s page is not exhaustive. It only lists co-authors who also have a Google Scholar profile. They also have to be suggested to the primary author and they need to accept the co-author to list them on the page.
From data sharing mandates to clinical trial registration, Open Science (OS) policies for biomedical research are in no short supply. But ensuring those policies become real-world practices can be a challenge—particularly when there’s no simple way to measure success.
So this happened: Zootaxa is a hugely important journal in animal taxonomy: On one hand one could argue that impact factor is a bad way to measure academic impact, so it's tempting to say this simply reflects a poor metric that is controlled by a commercial company using data that is not open.
Today we are pleased to announce that we have received new funding from the Gordon and Betty Moore Foundation. The $894k grant will help us improve infrastructure for R packages and enable us to move towards a science first package ecosystem for the R community. You may have already noticed some developments on this front when we announced our automated documentation server back in June.
A quick post this week. I write “this week” in an attempt to convince regular readers that weekly posting will continue. I noticed that J. Cell Sci. give download metrics for their papers and that these downloads are categorised into abstract, full-text and PDF. I was interested in how one of my papers performed.
Anyone that maintains a website is happy that people out there are interested enough to visit. Web traffic is one thing, but I take greatest pleasure in seeing quantixed posts being cited in academic papers. I love the fact that some posts on here have been cited in the literature more than some of my actual papers. It’s difficult to track citations to web resources.
I read this recent paper about very highly cited papers and science funding in the UK. The paper itself was not very good, but the dataset which underlies the paper is something to behold, as I’ll explain below. The idea behind the paper was to examine very highly cited papers in biomedicine with a connection to the UK. Have those authors been successful in getting funding from MRC, Wellcome Trust or NIHR?
This post is about a citation analysis that didn’t quite work out. I liked this blackboard project by Manuel Théry looking at the influence of each paper authored by David Pellman’s lab on the future directions of the Pellman lab.
Over the past week this tweet was doing the rounds. I’m not sure where it comes from or precisely what its original context was, but it appeared in my feed from folks in various student analytics and big data crowds. The message I took was “measurement looks complicated until you pin it down”. But what I took from this was something a bit different. Once upon a time the idea of temperature was a complex thing.