The text says one thing, but the graph they display to support their argument does not say what I thought it said. The purple line is supposed to be our "real" emissions, and the impression you get from the image and text is that our real emissions are much lower than the projected emissions. But if you actually look at the values of the purple line vs the other lines now , in 2020/2021, the values are almost exactly…
Great! So it's not just me! As I understand the paper, their main point seems to be that as you extrapolate out in time, you need to not just handle the physics of CO2 that is already in the atmosphere, but predict say how much populations will grow, as well as how much GDP will grow, and how CO2 emissions will be effected by that. So, say if there is an economic recession, then there will be less CO2 produced than if you predicted just say steady growth. This seems to be a case where I could see different assumptions (some reasonable) leading to different results--it's a far cry from say the breast cancer-vs skin-cancer mistake that he leads with
The text says one thing, but the graph they display to support their argument does not say what I thought it said. The purple line is supposed to be our "real" emissions, and the impression you get from the image and text is that our real emissions are much lower than the projected emissions. But if you actually look at the values of the purple line vs the other lines now , in 2020/2021, the values are almost exactly…
I think the point is that the actual emission are on the low side of the IPCC scenario bounds, and are tracking to exit completely the IPCC scenario bounds around 2021.
While this seems to give the impression that science is not functioning, I don't see this as the case. I will give an example from my field. Before Covid struck, I was at a conference in Japan. There was a talk about an interesting superconductor. Someone repeated some of the earlier measurements and determined that they were misinterpreted--that the measurement technique led to heating the material and thus the misinterpretation of the results and that the material wasn't so interesting after all. I think this was say 15-20 years after the original measurement. During the Q&A session, someone asked the original author what he thought. He stood up and said that the new measurement was correct. To me, that says science is working--it may work slowly, but over time, it does correct. Sure, there are people that take a long time convince (and sometimes they are never convinced), but science itself eventually corrects--but the challenge of new measurements that contradict the current consensus is that it's not that each one is correct--some are just measurement errors. For example, there was the case of a recent experiment that seemed to show faster than light travel of neutrinos. The authors presented it with the idea that there was a glitch somewhere that they couldn't find. After a flurry of papers (some with exotic new theories), they eventually were able to find the electronics glitch. It would have been exciting if they were correct--but they weren't--and science again worked.
The graph shows emissions trajectories projected by the most commonly used climate scenarios (called SSP5-8.5 and RCP8.5, with labels on the right vertical axis), along with other scenario trajectories. Actual emissions to date (dark purple curve) and those of near-term energy outlooks (labeled as EIA, BP and ExxonMobil) all can be found at the very low end of the scenario range, and far below the most commonly used…
From the article : "For instance, O’Neill and colleagues find that “many studies” use scenarios that are “unlikely.” In fact, in their literature review such “unlikely” scenarios comprise more than 20% of all scenario applications from 2014 to 2019. They also call for “re-examining the assumptions underlying” the high-end emissions scenarios that are favored in physical climate research, impact studies and economic a…
This sounds like good science being done. When you are trying to predict something like carbon emissions, standard practice is to run a few different scenarios. If you run 5 models, one with predicted CO2, and the others with higher and lower values, of course some of your scenarios will be unlikely. You're doing that on purpose so that you have a ability to see how wide the range of possible results is even with uncertainty in CO2.
Maybe off the wall, but my first thought is certificate revocation. Could there be (or is there already) a semi-centralized database of research that should no longer be cited? With maybe a dependency graph of research that maybe needs to be revisited?
This is part of what https://scite.ai/ is doing. They categorize citations as supporting, detracting, or neutral. The theory being you want to know if you’re citing something debunked. Scite also flags citations of retracted papers (and a Twitter bot that tweets when a new paper is published that cites a retracted study). And I think they have zotero integration (?)
I have no affiliation other than I have met the founder and think the product is cool.
This is a good read, although somewhat depressing. When you have a topic that has been weaponized politically, as climate change has, people who use that weapon actively work against information they perceive would make the weapon less effective. The author sums it up as follows: ---- from the article: According to Rayner, in such a context we should expect to see reactions to uncomfortable knowledge that include: de…
The entire opening of the article discussing 2020 papers erroneously using skin cancer data in breast cancer research papers which was a known error for at least 13 years - makes the point very strongly that " ... but these studies/experiments have shown that understanding to be incorrect. Now we believe this." happens much slower than perhaps people expect. I understand science "is expected to be wrong" sometimes, b…
Actually, the cell line issue might not be so bad or rather all cell line work is much worse than you all imagine.
No cell lines actually resemble the real tissue in gene expression if you say, do an rna screen and see what actuallg gets expressed. They are changed by line establishing process, use of various media, number of passages aka how long they’ve been in culture from thawing a line till the test (cant be too little or too much, requires line to recover after being frozen), person who’se culturing (some people tend to starve cells and passage full plates and have different parameters of work even despite some labwide protocols), adherence to the plate and growing in flat monoculture, getting plates out too much or watching them too lonv under the microscope. Some effects are temporary and not so serious. Some effects are rather serious. Like the fact that flat surface cell lines will never be a good proxy for the actual tumor growing in 3d in the actual human. That’s why people experimenting with spheres, multucultures with other cells, organelle cultures, animal models, and eventually all the clues from all the models add up to something that could be a theory of some mechanism. And then in most cases when applied to humans in real life it might not work or be harmful.
Now, the skin cell in cell media was likely arrayed and had features similar to breast cancer cells so it might have been okay to use for this super imperfect approximation.
Not sure if this particular instance. In vitro is only a part of it and peer reviewed journals differ in their authority ratings, with big boss journals like cell requiring you do deliver crazy amounts of different models to make any statement. Reading those papers is like reading house ads, scientists kind of learn to cut through bs
Maybe off the wall, but my first thought is certificate revocation. Could there be (or is there already) a semi-centralized database of research that should no longer be cited? With maybe a dependency graph of research that maybe needs to be revisited?
There's something quite like this in US law. If you are citing a case in a legal brief, you need to make sure it hasn't been overturned along the way, so you 'Shepardize' it. From Wikipedia [0]: Shepard's Citations is a citator used in United States legal research that provides a list of all the authorities citing a particular case, statute, or other legal authority. The verb Shepardizing refers to the process of con…
Maybe off the wall, but my first thought is certificate revocation. Could there be (or is there already) a semi-centralized database of research that should no longer be cited? With maybe a dependency graph of research that maybe needs to be revisited?
building that in Zotero would be great. I all ready like that they flag retracted papers.
The article is probably right about the bare facts, but it seems much like one of those that insist that Y2K was a big nothing, and that the Population Bomb fizzled. In each case, there was a warning that was followed by a phenomenal amount of hard work in back rooms to head off disaster. Disaster was headed off successfully, and then the people who had warned about it were criticized for their failed prediction. In…
Exactly. It is like your physician telling you if you keep drinking your liver will die. And a year later you proclaim: this guy is so unscientific, I stopped drinking, how come he didn't predict that.