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- Hacker News
- My read is that the model had too much variance; more regularization was needed.by esafak
- I'm confused as to what the actual issue was. What was the data for which Uzbekistan was the outlier and why?by tootie
- All else aside I mean how can they even claim to predict what an economy will do in 100 years anyway, it's going to adapt to complex higher order effects. Maybe climate change will increase GDP of everyone has to hire a worker to fan them with palm leaves.by noopprod
- Makes me wonder how many more papers out there have hard-to-pin-down errors like that
And how useful potentially AI could be to spot those (even if retrospectively)
by ktoyame - Good on them for the retraction. It's good to see science at work.by electroglyph
- Figure 1a (the leftmost subfigure in TFA’s lead image) shows the data for Uzbekistan from the DOSEv1 dataset (green), DOSEv2 dataset (red) and World Bank (black). The authors of the retracted study used the DOSEv2 dataset in order to model climate effects on the economy at a sub-national level, as opposed to the country-level analyses used in prior work. However, it looks like the DOSEv2 data was just bad for all 14 provinces in Uzbekistan (a 90% drop in GDP for all provinces in 2020!).
The typical correlation between weather and the economy is going to be fairly noisy across the dataset, but if you have 14 extra datapoints all saying there’s a catastrophic GDP crash in one year together with some coincidental weather effect, that’s going to bias the model hard. Notably, they also extrapolate losses forward all the way to 2100, so the effects of such a bias will compound.
by nneonneo - We need something akin to the international geophysical year, but for data integrity. Make it an interdisciplinary priority to clean house and root out papers that are hanging by a thread of included / excluded outliers, biased samples, and outright fraud. It would be humbling, but we'd be in much better shape afterwards.by MarkusQ
- > We wanted to see why Uzbekistan didn’t jump out, so we reproduced it in our comment (Extended Data Fig 1). It turns out that Uzbekistan wasn’t even the biggest outlier, but that the version they had published had the axes cropped so you couldn’t see the outliers (see red boxes in our version). This seemed indicative of a different issue, which is why we documented it in the comment.
Cropping the chart to hide the outliers is so bad that I can't tell if they're incompetent or malicious. I wouldn't be surprised if this is the kind of thing an LLM would produce in the hands of an operator not paying too much attention, but the paper was published in the time period before LLMs were everywhere in publishing.
by Aurornis