BorisVSchmid

Nice. Currently working with another probabilistic modelling extension of Clojure, named Anglican.

How would this compare to Anglican? (not so much in actual state of the library now, but in goals)

http://www.robots.ox.ac.uk/~fwood/anglican/

Somehow, physics does not appear to need such extensive vetting - to me (as an outsider) it seems like physicists can find what they need on arxiv.org

Hope that model successfully crosses over to biology (biorxiv.org). For now, I use the following heuristic after finding an article on google/google scholar:

* do I know the journal at all (to filter out vanity journals) * do I know the researchers involved (and I learn of new researchers through citations in papers, through presentations online or at conferences and through twitter) * I look at the number of citations of the paper (using google scholar) and relevance of the papers that already cite the paper of interest (using google scholar).

In addition, I also read papers :-).

Late reply, but ran into another plotting library, also from dvdt.

https://github.com/dvdt/gyptis

It is a nice wrapper around vega. Using that now.

Can we add some nuance here? It is not like in the last few decades there has been no new knowledge generated.

Just in my own field of biology, the amount of progress we have made in understanding how cells regulate themselves (20 year ago we were still teaching DNA->RNA->PROTEINS that do stuff), how immune systems function and can be used (stem cell therapy, cancer treatments, HIV drugs) and the flow of genetic information between organisms (the advance of (whole) genome sequencing into becoming a generic tool) has been mind-boggling.

As a scientist, I use a mix of Incanter, Quil, and gg4clj bridge to R's ggplot2 for visualization in clojure (none of these outputs to a browser though).

R's ggplot2 beats Incanter (or anything other charting library) by a large margin in its excellent mix of conciseness and power, but I find Quil pretty nice for animations (superimposing data on geographical maps, for example).

I keep an eye out for new charting libraries coming out for clojure. Last two I spotted were vizard from yieldbot (https://github.com/yieldbot/vizard), and what seems to have only been a small project, xvsy (https://github.com/dvdt/xvsy)

From my experience, scientists, -at least in biology, where like in sociology you might have a lot of noise to deal with-, have an internal intuition that a single paper with a significant result does not mean that we have found the truth. The recent study which reported a reproducibility in sociology of about 36% strikes me as pretty accurate.

I think the scientific system can work with that. It means that if you build follow-up experiments based on a single paper there is a good chance that the experiment fails. In some way, the scientific system of publishing is self-correcting in this regard, because you can then cast doubt on the previous paper, which is easier to publish than if you only have a fresh negative result (p-value > threshold).