In reflecting on the profound lack of association of grant percentile rank with the citations and quantity of the resulting papers, I am struck that it reinforces a point made by YHN about grant review.

I have never been a huge fan of the Approach criterion. Or, more accurately, how it is reviewed in practice. Review of the specific research plan can bog down in many areas. A review is often derailed off into critique of the applicant’s failure to appropriately consider all the alternatives, to engage in disagreement over the prediction of what can only be resolved empirically, to endless ticky-tack kvetching over buffer concentrations, to a desire for exacting specification of each and every control….. I am skeptical. I am skeptical that identifying these things plays any real role in the resulting science. First, because much of the criticism over the specifics of the approach vanish when you consider that the PI is a highly trained scientist who will work out the real science during the conduct of same. Like we all do. For anticipated and unanticipated problems that arise. Second, because there is much of this Approach review that is rightfully the domain of the peer review of scientific manuscripts.

I am particularly unimpressed by the shared delusion that the grant revision process by which the PI “responds appropriately” to the concerns of three reviewers alters the resulting science in a specific way either. Because of the above factors and because the grant is not a contract. The PI can feel free to change her application to meet reviewer comments and then, if funded, go on to do the science exactly how she proposed in the first place. Or, more likely, do the science as dictated by everything that occurs in the field in the years after the original study section critique was offered.

The Approach criterion score is the one that is most correlated with the eventual voted priority score, as we’ve seen in data offered up by the NIH in the past.

I would argue that a lot of the Approach criticism that I don’t like is an attempt to predict the future of the papers. To predict the impact and to predict the relative productivity. Criticism of the Approach often sounds to me like “This won’t be publishable unless they do X…..” or “this won’t be interpretable, unless they do Y instead….” or “nobody will cite this crap result unless they do this instead of that“.

It is a version of the deep motivator of review behavior. An unstated (or sometimes explicit) fear that the project described in the grant will fail, if the PI does not write different things in the application. The presumption is that if the PI does (or did) write the application a little bit differently in terms of the specific experiments and conditions, that all would be well.

So this also says that when Approach is given a congratulatory review, the panel members are predicting that the resulting papers will be of high impact…and plentiful.

The NHLBI data say this is utter nonsense.

Peer review of NIH grants is not good at predicting, within the historical fundable zone of about the top 35% of applications, the productivity and citation impact of the resulting science.

What the NHLBI data cannot address is a more subtle question. The peer review process decides which specific proposals get funded. Which subtopic domains, in what quantity, with which models and approaches… and there is no good way to assess the relative wisdom of this. For example, a grant on heroin may produce the same number of papers and citations as a grant on cocaine. A given program on cocaine using mouse models may produce approximately the same bibliometric outcome as one using humans. Yet the real world functional impact may be very different.

I don’t know how we could determine the “correct” balance but I think we can introspect that peer review can predict topic domain and the research models a lot better than it can predict citations and paper count. In my experience when a grant is on cocaine, the PI tends to spend most of her effort on cocaine, not heroin. When the grant is for human fMRI imaging, it is rare the PI pulls a switcheroo and works on fruit flies. These general research domain issues are a lot more predictable outcome than the impact of the resulting papers, in my estimation.

This leads to the inevitable conclusion that grant peer review should focus on the things that it can affect and not on the things that it cannot. Significance. Aka, “The Big Picture”. Peer review should wrestle over the relative merits of the overall topic domain, the research models and the general space of the experiments. It should de-emphasize the nitpicking of the experimental plan.

A reader pointed me to this News Focus in Science which referred to Danthi et al, 2014.

Danthi N1, Wu CO, Shi P, Lauer M. Percentile ranking and citation impact of a large cohort of national heart, lung, and blood institute-funded cardiovascular r01 grants. Circ Res. 2014 Feb 14;114(4):600-6. doi: 10.1161/CIRCRESAHA.114.302656. Epub 2014 Jan 9.

[PubMed, Publisher]

I think Figure 2 makes the point, even without knowing much about the particulars
Danthi14-Fig2

and the last part of the Abstract makes it clear.

We found no association between percentile rankings and citation metrics; the absence of association persisted even after accounting for calendar time, grant duration, number of grants acknowledged per paper, number of authors per paper, early investigator status, human versus nonhuman focus, and institutional funding. An exploratory machine learning analysis suggested that grants with the best percentile rankings did yield more maximally cited papers.

The only thing surprising in all of this was a quote attributed to the senior author Michael Lauer in the News Focus piece.

“Peer review should be able to tell us what research projects will have the biggest impacts,” Lauer contends. “In fact, we explicitly tell scientists it’s one of the main criteria for review. But what we found is quite remarkable. Peer review is not predicting outcomes at all. And that’s quite disconcerting.”

Lauer is head of the Division of Cardiovascular Research at the NHLBI and has been there since 2007. Long enough to know what time it is. More than long enough.

The take home message is exceptionally clear. It is a message that most scientist who have stopped to think about it for half a second have already arrived upon.


Science is unpredictable.

Addendum: I should probably point out for those readers who are not familiar with the whole NIH Grant system that the major unknown here is the fate of unfunded projects. It could very well be the case that the ones that manage to win funding do not differ much but the ones that are kept from funding would have failed miserably, had they been funded. Obviously we can’t know this until the NIH decides to do a study in which they randomly pick up grants across the entire distribution of priority scores. If I was a betting man I’d have to lay even odds on the upper and lower halves of the score distribution 1) not differing vs 2) upper half does better in terms of paper metrics. I really don’t have a firm prediction, I could see it either way.

Nature editor Noah Gray Twittered a link to a 2003 Editorial in Nature Neuroscience.

The key takeaway is in the figure (which Noah also twittered).

Image

In 2003 the JIF for Nature Neuroscience was 15.14, for J Neuro 8.05 and for Brain Research 2.474. Nature itself was 30.98.

Plenty of people refer to the skew and the relative influence of a handful of very highly cited papers but it is interesting and more memorable to see in graphical form, isn’t it?

 

As far as I can tell, the British Journal of Pharmacology has taken to requiring that authors who use animal subjects conduct their studies in accordance with the “ARRIVE” (Animals in Research: Reporting In Vivo Experiments) principles. These are conveniently detailed in their own editorial:

McGrath JC, Drummond GB, McLachlan EM, Kilkenny C, Wainwright CL.Guidelines for reporting experiments involving animals: the ARRIVE guidelines.Br J Pharmacol. 2010 Aug;160(7):1573-6. doi: 10.1111/j.1476-5381.2010.00873.x.

and paper on the guidelines:

Kilkenny C, Browne W, Cuthill IC, Emerson M, Altman DG; NC3Rs Reporting Guidelines Working Group.Animal research: reporting in vivo experiments: the ARRIVE guidelines. Br J Pharmacol. 2010 Aug;160(7):1577-9. doi: 10.1111/j.1476-5381.2010.00872.x.

The editorial has been cited 270 times. The guidelines paper has been cited 199 times so far and the vast, vast majority of these are in, you guessed it, the BRITISH JOURNAL OF PHARMACOLOGY.

One might almost suspect the journal now has a demand that authors indicate that they have followed these ARRIVE guidelines by citing the 3 page paper listing them. The journal IF is 5.067 so having an item cited 199 times since it was published in the August 2010 issue represents a considerable outlier. I don’t know if a “Guidelines” category of paper (as this is described on the pdf) goes into the ISI calculation. For all we know they had to exempt it. But why would they?

And I notice that some other journals seem to have published the guidelines under the byline of the self same authors! Self-Plagiarism!!!

Perhaps they likewise demand that authors cite the paper from their own journal?

Seems a neat little trick to run up an impact factor, doesn’t it? Given the JIT and publication rate of real articles in many journals, a couple of hundred extra cites in the sampling interval can have an effect on the JIT.

Naturally this is a time for a resurgence of blathering about how Journal Impact Factors are a hugely flawed measure of the quality of individual papers or scientists. Also it is a time of much bragging about recent gains….I was alerted to the fact that they were out via a society I follow on Twitter bragging about their latest number.

whoo-hoo!

Of course, one must evaluate such claims in context. Seemingly the JIF trend is for unrelenting gains year over year. Which makes sense, of course, if science continues to expand. More science, more papers and therefore more citations seems to me to be the underlying reality. So the only thing that matters is how much a given journal has changed relative to other peer journals, right? A numerical gain, sometimes ridiculously tiny, is hardly the stuff of great pride.

So I thought I’d take a look at some journals that publish drug-abuse type science. There are a ton more in the ~2.5-4.5 range but I picked out the ones that seemed to actually have changed at some point.
2012-ImpactFactor1
Neuropsychopharmacology, the journal of the ACNP and subject of the abovequoted Twitt, has closed the gap on arch-rival Biological Psychiatry in the past two years, although each of them trended upward in the past year. For NPP, putting the sadly declining Journal of Neuroscience (the Society for Neuroscience’s journal) firmly behind them has to be considered a gain. J Neuro is more general in topic and, as PhysioProf is fond of pointing out does not publish review articles, so this is expected. NPP invented a once-annual review journal a few years ago and it counts in their JIF so I’m going to score the last couple of years’ of gain to this, personally.

Addiction Biology is another curious case. It is worth special note for both the large gains in JIF and the fact it sits atop the ISI Journal Citation Reports (JCR) category for Substance Abuse. The first jump in IF was associated with a change in publisher so perhaps it started getting promoted more heavily and/or guided for JIF gains more heavily. There was a change in editor in there somewhere as well which may have contributed. The most recent gains, I wager, have a little something to do with the self-reinforcing virtuous cycle of having topped the category listing in the ISI JCR and having crept to the top of a large heap of ~2.5-4.5 JIF behavioral pharmacology / neuroscience type journals. This journal had been quarterly up until about two years ago when it started publishing bimonthly and their pre-print queue is ENORMOUS. I saw some articles published in a print issue this year that had appeared online two years before. TWO YEARS! That’s a lot of time to accumulate citations before the official JIF window even starts counting. There was news of a record number of journals being excluded from the JCR for self-citation type gaming of the index….I do wonder why the pre-print queue length is not of concern to ISI.

PLoS ONE is an interest of mine, as you know. Phil Davis has an interesting analysis up at Scholarly Kitchen which discusses the tremendous acceleration in papers published per year in PLoS ONE and argues a decline in JIF is inevitable. I tend to agree.

Neuropharmacology and British Journal of Pharmacology are examples of journals which are near the top of the aforementioned mass of journals that publish normal scientific work in my fields of interest. Workmanlike? I suppose the non-perjorative use of that term would be accurate. These two journals bubbled up slightly in the past five years but seem to be enjoying different fates in 2012. It will be interesting to see if these are just wobbles or if the journals can sustain the trends. If real, it may show how easily one journal can suffer a PLoS ONE type of fate whereby slightly elevated JIF draws more papers of a lesser eventual impact. While BJP may be showing the sort of virtuous cycle that I suspect Addiction Biology has been enjoying. One slightly discordant note for this interpretation is that Neuropharmacology has managed to get the online-to-print publication lag down to some of the lowest amongst its competition. This is a plus for authors who need to pad their calendar-year citation numbers but it may be a drag on the JIF since articles don’t enjoy as much time to acquire citations.

As you know, I have a morbid fascination with PLoS ONE and what it means for science, careers in science and the practices within my subfields of interest.

There are two complaints that I see as supposed objective reasons for old school folks’ easy complaining bout how it is not a real journal. First, that they simply publish “too many papers”. It was 23,468 in 2012. This particular complaint always reminds me of

which is to say that it is a sort of meaningless throwaway comment. A person who has a subjective distaste and simply makes something up on the spot to cover it over. More importantly, however, it brings up the fact that people are comparing apples to oranges. That is, they are looking at a regular print type of journal (or several of them) and identifying the disconnect. My subfield journals of interest maybe publish something between about 12 and 20 original reports per issue. One or two issues per month. So anything from about 144 to 480 articles per year. A lot lower than PLoS ONE, eh? But look, I follow at least 10 journals that are sort of normal, run of the mill, society level journals in which stuff that I read, cite and publish myself might appear. So right there we’re up to something on the order of 3,000 article per year.

PLoS ONE, as you know, covers just about all aspects of science! So multiply my subfield by all the other subfields (I can get to 20 easy without even leaving “biomedical” as the supergroup) with their respective journals and…. all of a sudden the PLoS ONE output doesn’t look so large.

Another way to look at this would be to examine the output of all of the many journals that a big publisher like Elsevier puts out each year. How many do they publish? One hell of a lot more that 23,000 I can assure you. (I mean really, don’t they have almost that many journals?) So one answer to the “too many notes” type of complaint might be to ask if the person also discounts Cell articles for that same reason.

The second theme of objection to PLoS ONE is as was recently expressed by @egmoss on the Twitts :

An 80% acceptance rate is a bit of a problem.

So this tends to overlook the fact that much more ends up published somewhere, eventually than is reflected in a per-journal acceptance rate. As noted by Conan Kornetsky back in 1975 upon relinquishing the helm of Psychopharmacology:

“There are enough journals currently published that if the scientist perseveres through the various rewriting to meet style differences, he will eventually find a journal that will accept his work”.

Again, I ask you to consider the entire body of journals that are normal for your subfield. What do you think the overall acceptance rate for a given manuscript might be? I’d wager it is competitive with PL0S ONE’s 80% and probably even higher!

So one of the Twitts was recently describing a grant funding agency that required listing the Impact Factor of each journal in which the applicant had published.

No word on whether or not it was the IF for the year in which the paper was published, which seems most fair to me.

It also emerged that the applicant was supposed to list the Journal Impact Factor (JIF) for subdisciplines, presumably the “median impact factor” supplied by ISI. I was curious about the relative impact of listing a different ISI journal category as your primary subdiscipline of science. A sample of ones related to the drug abuse sciences would be:

Neurosciences 2.75
Substance Abuse 2.36
Toxicology 2.34
Behavioral Sciences 2.56
Pharmacology/Pharmacy 2.15
Psychology 2.12
Psychiatry 2.21

Fascinating. What about…
Oncology 2.53
Surgery 1.37
Microbiology 2.40
Neuroimaging 1.69
Veterinary Sciences 0.81
Plant Sciences 1.37

aha, finally a sub-1.0. So I went hunting for some usual suspects mentioned, or suspected, as low-cite rate disciplines..
Geology 0.93
Geosciences, multidisc 1.33
Forestry 0.87
Statistics and Probability 0.86
Zoology 1.06
Forestry 0.87
Meteorology 1.67

This a far from complete list of the ISI subdisciplines (and please recognize that many journals can be cross-listed), just a non-random walk conducted by YHN. But it suggests that range is really restricted, particularly when it comes to closely related fields, like the ones that would fall under the umbrella of substance abuse.

I say the range is restricted because as we know, when it comes to journals in the ~2-4 IF range within neuroscience (as an example), there is really very little difference in subjective quality. (Yes, this is a discussion conditioned on the JIF, deal.)

It requires, I assert, at least the JIF ~6+ range to distinguish a manuscript acceptance from the general herd below about 4.

My point here is that I am uncertain that the agency which requires listing disciplinary medians JIFs is really gaining an improved picture of the applicant. Uncertain if cross-disciplinary comparisons can be made effectively. You still need additional knowledge to understand if the person’s CV is filled with Journals that are viewed as significantly better than average within the subfield. About all you can tell is that they are above or below the median.

A journal which bests the Neurosciences median by a point (3.75) really isn’t all that impressive. You have to add something on the order of 3-4 IF points to make a dent. But maybe in Forestry if you get to only a 1.25 this is a smoking upgrade in the perceived awesomeness of the journal? How would one know without further information?