[andrewp123]

Always depressing to see a paper like this. I can almost guarantee one could make this whole thing into a two-page document with a clearer vision and followable to, well, anyone else.

The purpose of academic papers is to file a claim to ownership of ideas / progress. But it would be cool if in another place they published the intuitions they used to come up with the claim in the first place.

[barfbagginus]

Boolean networks and petri nets have been important in biology since the 60s and 70s. If you don't know that history, there are thousands of papers and books to get you up to speed with the intuition and practice behind them. You should not be depressed when you meet a topic with a long history like this - the history is usually linked in the papers own bibliography. Get reading instead!

You are wrong about what science papers are - they're more than just territory markers to claim ownership of ideas. They also explain the idea and get people interested in building on it and using it to create value for humanity.

This paper is pretty simple and sweet, but it needs more than a couple pages to:

1. Define trap spaces and sketch their history and usefulness

2. Prove they're equivalent to conflict free siphons

3. Explore some ways to calculate siphons

4. Show that these ways all beat the pants off existing trap space methods

This is all intuitive - and there are a bunch of references in the bibliography if you want to learn more. One reference is the author's earlier work, which should have more intuition, but less polish, than the current paper.

We could criticize the work. The author clearly took their proof from an earlier paper, bolted some benchmarks onto it, and republished it. And unless we're experts, we have to trust the author included the best possible competing solutions in that benchmark.

But assuming the author is honest, the benchmarks are impressive. It took serious work to implement their methods and build the benchmark. So it's hard to hate the author here for consolidating their win.

To really criticize the paper - and see if it's as useful as the tests suggest - we'd want to run the experiment and verify the competing techniques represent the state of the art and were configured correctly. It would be fun!

I encourage you to learn how to read science. Science does need our criticism and contribution, very much so. But before we can criticize it constructively, we must care about a specific topic, and educate ourselves as much as possible. It doesn't help humanity to give cookie cutter criticisms about papers we don't care about. Let's unleash criticism that gives true value to humanity, and extends what science can do!

[dullcrisp]

Is your premise that everything can be accessible to everyone with no prior training or am I misunderstanding what you’re saying?

[hwbehrens]

I don't think that was the grandparent's premise, but I actually think that it's not unreasonable to expect experts to be able to boil down their ideas for non-experts.

We know it must be possible, because they themselves arrived at that point in an abstract "graph of knowledge" starting from a blank slate at birth, so going the other direction is (at worst) merely backtracking that path. However, most experts know enough other nodes/edges in the graph to identify shortcuts from their conclusion back toward the 'beaten path' that most people would know.

I often argue that if you aren't able to articulate the core idea of your research to someone outside your field, you might not understand it as well as you think you do.

(Re: the grandparent) When communicating with the scientific community, however, it's not unreasonable to be as precise as possible to convey the idea accurately to fellow experts. Replacing scientific papers with blog posts is not a good solution; augmenting scientific papers with blog posts might be appropriate.