Like many other people, I have wasted a lot of time trying to reimplement models in the literature. Sometimes it succeeds, sometimes it fails, but the time it takes is always significant.

I'm thinking of 3 examples off the top of my head...

1. An ODE model with ~10 equations. No code. I reimplemented it and exactly reproduced the plots from the paper. I assume this would be good for ReScience. I'll try to clean it up and submit it this weekend.

2. Another ODE model with ~10 equations. No code. I reimplemented it as best I could, but it doesn't quite reproduce the figures in the paper. Typo in my code? Typo in the paper? No way to know. Is there any place for something like that?

3. A stochastic model with ~4 equations. No code. I reimplemented it as best I could, but because it's stochastic, it's hard to say if it's exactly what the authors originally made. Now here's the interesting part... if I run the model 10 times, naturally I get 10 different outputs. Maybe 1 or 2 will be nice and pretty like the plots in the paper. The other ones look kind of shitty. Is that evidence that the authors ran their model a bunch of times and picked only the nicest looking results for the paper? Or is it evidence that my implementation isn't quite right? I don't know. Is there anything I can do with that code?