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.<p>I&#x27;m thinking of 3 examples off the top of my head...<p>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&#x27;ll try to clean it up and submit it this weekend.<p>2. Another ODE model with ~10 equations. No code. I reimplemented it as best I could, but it doesn&#x27;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?<p>3. A stochastic model with ~4 equations. No code. I reimplemented it as best I could, but because it&#x27;s stochastic, it&#x27;s hard to say if it&#x27;s exactly what the authors originally made. Now here&#x27;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&#x27;t quite right? I don&#x27;t know. Is there anything I can do with that code?