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Respectfully, I think you're missing the complications outlined in the rest of the thread. The difficulty in the biosciences and even in chemistry and some phys
by entee 10y ago
Respectfully, I think you're missing the complications outlined in the rest of the thread. The difficulty in the biosciences and even in chemistry and some physics is that they can't really be formalized in the way that is necessary to construct these "chains of proof".
The scientific literature is an ongoing conversation anchored by rigorous experimental facts and data. But rigorous doesn't mean it's clean like a mathematical proof. In fact, most science approaches its "proofs" in quite a different way than math. For example, as far as science would be concerned P!=NP in complexity theory. We've done the experiment many times, tried different things, it's pretty much true. But it's still not mathematically proven because there isn't a formal proof.
That's not to say it's invalid to expect more rigor, or that we wouldn't all love to have "chains of proof" and databases and signatures for data etc. It's that it's simply not practical given how noisy and complex biological systems are. In contrast to math, you pretty much never know the full complement of objects/chemicals/parameters in your experimental space. You try to do the right controls to eliminate the confounding variables, but you're still never fully in control of all the nobs and switches in your system. That's why usually you need multiple different experiments tackling a problem from multiple different approaches for a result to be convincing.
Formalized systems would be great, but I don't think we're even close to understanding how to properly formalize all of those difficulties and variables in a useful way. And it may not even be possible.
- dorgo 10y agoI thought that statistics is the right tool to handle uncertainity? I had the impression that all the "soft" science is based on statistics. We can't prove that smoking kills people. But, given a certain confidance interval (or whatever equivalent measure for baysian statistics?), we can state that smoking is not a good idea if you want to live longer than mean expected years... Sure, some unforseen event may interfere with your experiment. But statistics should account for that, shouldn't it? Just wondering..
- epistasis 10y agoStatistics is also the way to look at data in the "hard" sciences. Every measurement has error, and that's how you deal with it. However it's not a simple thing that automatically combines different studies. It takes skilled application to understand how data connects, what's comparable, what's not, etc. Traditionally, "meta-analysis" is the sub-field of statistics that combines studies. But that only combines extremely simple studies, such as high-controlled clinical trials. It's inappropriate for the complex type of data that appears in a typical molecular biology paper is a chain of lots of different types of experimental setups. Those who don't know the body of stats, trying to reason about application, is a lot like an MBA trying to reason about software architecture. The devil is in the details, and the details are absolutely 100% important with application of statistics to data.
- Balgair 10y agoAmen. You can google the controversy around the StatCheck program to really dive into why stats and their applications are beyond lies and damned-lies in their falsehoods (because you can prove the lie is right). Doing something as simple as smoking causes cancer is a very very simple experiment to interpret (hard to fund/preform though). It's the pernicious little studies on 8 cells total that get messy. Preforming a lot of experiments is hard. I knew of a student that graduated with only 8 cells of data out of his 7 years in grad school. That may sound like a small amount, but to his committee, it was a very impressive number. He (very very) basically sliced up adult rodent brains and then used super tiny glass pipettes to poke the insides of certain cells. He chemically altered these cells' insides in a hopefully intact network of neurons, shocked the cells, and then recorded the activity of other cells in the network using the same techniques. Then he preserved and stained the little brain slice so he could confirm his results anatomically. From start to finish, it took him 13 hours total, no lunch or restroom breaks, every day, for 7 years. He got 8 confirmable cells worth of recordings total. That is a hard experiment. But due to his efforts in adding evidence we now suspect that most adult hearing loss is not due to loss of cells in the ear, but in the coordination of signals to the brain and their timing mis-match. It is not much, bu it adds to the evidence and will for sure help out people someday. To add, he is now a beer brewer in Bavaria and quit science. This shit takes sacrifice man.
- FabHK 10y agoWhat a crazy story. I want a beer from that dude.
- vacri 10y ago> I had the impression that all the "soft" science is based on statistics. In medicine, case studies are often used for low n issues. There are too many variables for meaningful statistics to be pulled out, but a "this patient had X, we did Y, Z happened" is still a way to pass on observational information. It's recognised that case studies aren't ideal, but it's still better than not passing on information at all.
- ivan_gammel 10y agoEverything can be formalized, even uncertainties in knowledge about experimental environment (e.g. by making a statement that unaccounted parameters do not influence the result - indeed, this will be challenged and proof requested and things like fire alarm affecting mice behavior should be reliably excluded). Something that cannot be formalized, cannot be proven or falsified and thus is not a science. The only difficulty may be to build the necessary apparatus, but that's doable and that's the way to fix the science.
- Balgair 10y agoUmm, no. Look at Godel's Incompleteness Theorem. You can prove that you will always be able to make a paradox in any formalized system of logic; at least, under our current understanding of logic. Expanding that (Godel, Escher, Bach by Hoffseader goes into it well) you then can say that any theory of the universe must have holes in it and any machine or system that attempts to formalize the observations will always come up with paradoxes. You are right, you can formalize everything (maybe, jury is still out on that, but I think so), but at the risk of then making paradoxes in the system.
- ivan_gammel 10y agoI'm aware of this theorem and it has nothing to do with scientific method, it only gives us an idea of possible results of research and it does not tell us that you cannot formalize life sciences or chemistry. Indeed, there are theories that cannot be proven, but they are itself subject to formalization and research.
- chriswarbo 10y agoWhilst the experimental subjects and data collection are inherently fraught with difficulty, there's still a LOT of low-hanging fruit regarding things like automation. Many scientists use computers to write up results, to store data and perform calculations, but there's often a lot of manual, undocumented work which could easily be scripted to help those re-running the experiment. For example, running some program to produce a figure, without documenting what options were used; providing a CSV of data, without the formulas used for the aggregate statistics; relying on a human to know that the data for "fig1.png" comes from "out.old-Restored_Backup_2015~"; etc. Such scripting is a step on the path to formalising methods. They'd help those who just want to see the same results; those who want to perform the same analysis using some different data; those who want to investigate the methods used, looking for errors or maybe doing a survey of the use of statistics in the field; those who want a baseline from which to more thoroughly reproduce the experiment/effect; etc. The parent's list of mouse-frighteners reminds me of the push for checklists in surgery, to prevent things like equipment being left inside patients. Whilst such lists are too verbose for a methods section (it would suffice to say e.g. "Care was taken to ensure the animals were relaxed."), there's no reason the analysis scripts can't prompt the user for such ad hoc conditions, e.g. "Measurements should be taken from relaxed animals. Did any alarms sound in the previous 24 hours? y/N/?", "Were the enclosures relatively clean? Y/n/?", "Were the enclosures cleaned out in the previous 24 hours? y/N/?", etc. with output messages like "Warning: Your answers indicate that the animals may not have been relaxed during measurements. If the following results aren't satisfactory, consider ..." or "Based on your answers, the animals appear to be in a relaxed state. If you discover this was not the case, we would appreciate if you update the file 'checklist.json' and send your changes to 'experimentABC@some-curator.org'. More detailed instructions can be found in the file 'CONTRIBUTING.txt'"