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Still waiting for an open discussion forum for scientific papers. Like StackOverflow, but every post is a paper. And there are experts of various gradations that help with questions.
Still waiting for an open discussion forum for scientific papers. Like StackOverflow, but every post is a paper. And there are experts of various gradations that help with questions.
Still waiting for an open discussion forum for scientific papers. Like StackOverflow, but every post is a paper. And there are experts of various gradations that help with questions.
I said a few days ago, in my dream HN would be mostly papers. That's where the richest, most accurate, most intellectually curious information is - far beyond most things on HN.
This misses the best skimming trick I learned from an advisor: After you read the abstract, read the last couple lines/paragraphs of the introduction. That's where you'll find the authors best summary of the paper's contributions and novelty. For instance, the first paper that popped up with some random search terms [0]: The present paper attempts to provide a structured and comprehensive overview of state-of-the-art…
The second paragraph says:
>I start by reading the abstract. Then, I skim the introduction [...]
A few paragraphs down, another quote says:
>I always start with title and abstract. [...] I then read the introduction [...]
Another:
>I nearly always read the abstract first [...] I generally skim the introduction, reading its last paragraph
Is there something significantly different about what you are suggesting?
This misses the best skimming trick I learned from an advisor: After you read the abstract, read the last couple lines/paragraphs of the introduction. That's where you'll find the authors best summary of the paper's contributions and novelty. For instance, the first paper that popped up with some random search terms [0]: The present paper attempts to provide a structured and comprehensive overview of state-of-the-art…
The fundamental problem with abstracts and introductions is that they're sales content. You can't trust them. The only thing you can do is decide if you wish to read further, and see if the paper says what they claim it says. For that, an abstract is sufficient about 99% of the time. Spending lots (or...any amount) of time on the intro before you read the data tables is basically asking to have time stolen from you.
For what it's worth, the proportion of papers where the body doesn't support the claims in the abstract is...high. Like way above 50%, in my experience (approaching nearly 100% for any random paper you find on HN or X.)
My algorithm is:
* read abstract. decide to continue.
* formulate my own version of the experiment in my head -- how would I go about answering this question?
* read all data tables, including supplemental materials. see if anything stands out as weird.
* look at all figures, including supplemental materials. see if anything stands out as weird.
* do I understand the data? if not, search for table/figure references from results, until I do (generally I end up reading most of the results, out-of-order).
* is this paper consistent with the way I'd have approached the problem? If not, is that important? what are the possible methodological flaws? what would they look like in the data?
* re-examine data to look for signs of flaws.
* does the data support the conclusion? if not, why not? what would I do differently or as a follow-up?
* finally, decide if the paper worth reading in detail.
Still waiting for an open discussion forum for scientific papers. Like StackOverflow, but every post is a paper. And there are experts of various gradations that help with questions.
Individual subreddits have usually been my go-to place to discuss and understand the nuances of academic papers. Love LocalLLama for discussions on generative AI papers.
This says so much about the volume of absolute crap that gets published in Science. No competent editor-in-chief should be looking to the news media to give background on a research topic.
This misses the best skimming trick I learned from an advisor: After you read the abstract, read the last couple lines/paragraphs of the introduction. That's where you'll find the authors best summary of the paper's contributions and novelty. For instance, the first paper that popped up with some random search terms [0]: The present paper attempts to provide a structured and comprehensive overview of state-of-the-art…
Maybe it depends on the literature. I almost never read the introduction, unless I am unclear on the motivation for the work from the abstract. The fundamental problem with abstracts and introductions is that they're sales content . You can't trust them. The only thing you can do is decide if you wish to read further, and see if the paper says what they claim it says. For that, an abstract is sufficient about 99% of…
> As editor-in-chief of Science....Generally, I start with the corresponding editors' summaries, which are meant for someone like me: a science generalist who is interested in everything but dives deeply only into one field. Next, I check to see if someone wrote a News article on the paper. Third, I check to see if there is a Perspective by another scientist. This says so much about the volume of absolute crap that g…
This misses the best skimming trick I learned from an advisor: After you read the abstract, read the last couple lines/paragraphs of the introduction. That's where you'll find the authors best summary of the paper's contributions and novelty. For instance, the first paper that popped up with some random search terms [0]: The present paper attempts to provide a structured and comprehensive overview of state-of-the-art…
Maybe I'm misunderstanding what you mean, but I don't think your trick was missed at all? The second paragraph says: > I start by reading the abstract. Then, I skim the introduction [...] A few paragraphs down, another quote says: > I always start with title and abstract. [...] I then read the introduction [...] Another: > I nearly always read the abstract first [...] I generally skim the introduction, reading its la…