Yet, you also find it plausible that people who spent years on this project would never have thought of that.
Your misplaced trust in your own plausibility filter causes you to make foolish posts on HN.
Your misplaced trust in your own plausibility filter causes you to make foolish posts on HN.
I find it plausible that the few people who spent hours reviewing this paper didn't think of that, and that the people publishing the paper ignored it since ignoring it could help them gain more funding.
> Your misplaced trust in your own plausibility filter causes you to make foolish posts on HN.
It is foolish to believe that scientists does things properly. As an outsider you only see the outlier results, meaning that most of what reaches HN could be faked or statistical trickery or have simple explanations due to poor science since poor science is more likely to produce headlines, while most scientists could still do the right thing.
But their mistakes are generally subtle, and not what somebody who knows nothing about the subject invents in the first seconds after first hearing about the topic.
The primary COVID model that triggered lockdowns was full of programming errors. It had never been peer reviewed, and its prediction of deaths varied by 80,000 depending on whether you engaged a data loading optimization or not. It gave totally different results depending on available CPU features! There were no tests and the results had never been validated against anything. Outsiders pointed out these problems, and the team didn't care, nor did anyone else in the field of epidemiology.
That's just one example of many. Epidemiology is kinda like the phrenology of our era (one of quite a few). It's not built on a firm scientific foundation.