With exactly 13 hours to go before the close of bets, the betting pool for minimum Arctic sea ice looks like this:
Only Doc is still mathematically eliminated.
We all know that crackpots have a number of identifying features. These have been enumerated on other blogs; I won’t rehash that material. However, I would like to examine one particular point.
When crackpots compare themselves to great scientists, it is almost always to Galileo. As he was a persecuted genius ahead of his time, this is not surprising. This is how crackpots self-identify. But Galileo was not the only scientist in such a situation. Even in the limited field of 17th century astronomy, Tycho Brahe was in the same category.
Brahe, the last great pre-telescope observer, mapped the night sky to a precision not seen for another century. He had by far the best dataset of the time period, and while Galileo had to deal with house arrest in his later years, Tycho was poisoned, either by his king for being an embarrassment, or by Kepler for not handing over his data.
So why aren’t there more wannabe Tychos?
I think the key is their perceived contributions. While Tycho is seen as having been a meticulous, workaholic data collector, Galileo is often thought of as a guy with a single flash of cross-disciplinary brilliance that changed everything. Just point this navigational aid into the night sky, and BLAM! The universe has changed.
Of course, this interpretation overlooks the huge effort that Galileo put in, but we’re taking about perception here. His lens grinding, observing schedule, and other elbow grease producing work is generally less emphasized than his brilliant idea is.
So why does this appeal to crackpots? Because. They don’t just want to be game-changing scientists; they want it to be easy. I’ve never seen a crackpot whose theory required years and years of dawn-to-dusk data. Crackpot theories invariable offer simple, pat solutions that obviate the need for further rigorous study. The whole point of having a simple explain everything theory is so that they can go around feeling smug without having to crunch through weeks of data analysis. There are no crackpot Tychos because he is seen to have worked too hard to be a role model for them. Crackpotism isn’t just intellectual laziness; it’s ordinary laziness too.
I recently skimmed a PhD thesis which contained attempts at geochronology of some unconventional uranium ore minerals. The U concentrations in the data table ranged from about 400000 ppm to about 1700000 ppm, with a mean around 1100000. Now, I am the last person on Earth who has a right to complain about imperfections in a PhD thesis. Indeed, one of the reasons that you are reading these autoqueue posts is that I'm rereducing some of my PhD data from scratch to get it publication worthy. But still. More than a million ppm? Evidently it passed the review in this form, although it is possible that we were looking at a pre-corrections copy. Still. An A for effort, perhaps? Or evidence that in addition to the traditional pass/ pass with corrections/ fail categories, we also need an option to "fail, and send back to 7th grade."
40 years ago today, the Apollo astronauts splashed down in the Pacific Ocean after visiting the moon. While it is nice that they went there, it is even better that they came back. Especially since they brought rocks with them.
The scientific return from the Apollo mission is often understated. Just the other day, Mark at Cosmic Variance said "But what grabbed me was the exploration, and the adventure. Not the science.". But while it is true that the mission was not designed as a scientific experiment, the scientific return was nothing short of phenomenal.
There were a number of non-geologic accomplishments of the mission- such as the first collection and return of solar wind, and various discoveries relating to lunar ranging, etc. But the rocks alone are worth considering.
"...and all we brought back were some rocks." is a common criticism on the Apollo program. Of course, geology isn't about the rocks. Geology is about the stories rocks tell. And what a story.
Prior to the return of Apollo 11, people really had no idea what the Moon was made of, nor how it got there. Based on Terrestrial geology, people made various educated guesses about the composition and origin of the moon. And they were all wrong.
Earth is thought to have formed by the collisions of tens to hundreds of smaller bodies. In contrast, the Moon condensed from material vaporized during one of these Earth-forming collisions. It then cooled, crystallized, and aside from some sporadic magmatism, had done little else since.
Despite being co-genetic with the Earth, the Moon is completely and totally different. In fact, it is so different as to be beyond any of the theories dreamed up prior to the return of the Moon rocks. As such, it set a pattern for the characterization of other planetary bodies- first in our own solar system, and more recently, around far away stars. Time and time again, planets defy our expectations. The geysers of Triton and Enceladus. Perchlorates on Mars. The extreme eccentricity and small orbits of extrasolar planets.
The key revelation from Apollo- which has been repeated every time planetary science has stepped farther out into the galaxy- is this:
Planetary formation is stochastic. Planets are not like aluminum atoms, electrons, or whatever-it-is that the LHC is supposed to discover. There is no formula you can devise to predict the details of all the planets in the Galaxy. They are not interchangeable. You have to actually go out and observe them, in order to figure out their stories. This lesson was first learned from the Apollo samples, and it is incredible important. Because every time scientists forget it, the universe shows them up.
With about 9 days to go, the pool looks like this:
Here are the guesses, in no particular order:
5200 ±75
4555 ±60
4150 ±100
4800 ±75
4675 ±65
4900 ±80
4700 ±50
4700 ±200
3900 ±100
4250 ±100
4300 ±100
4000 ±75
5325 ±75
4400 ±100
4600 ±100
4000 ±100
4920 ±500
4535 ±25
4235 ±100
4000 ±350
Those guesses which have been mathematically eliminated at the 2 sigma level are dotted. As the rules allow for eliminated contestants to re-guess, Doc and Alistair may guess again if they so desire.
In order to help people guess intelligently, the Y axis has been labeled to show the maximum value of a curve of given sigma. As you can see, guessing with an uncertainty of ± 200 in the well populated areas of the pool will not be very productive.
Contest ends at the beginning of August UTC time. Rules and original announcement are here.
Please put any additional guesses in this thread, giving value, sigma, preferred color, and a bit about your background.
As previously stated, guesses are to be in the form of extent and sigma (a mathematical measure of uncertainty), in thousands of km2 You may use decimal places if you insist.
Your guess will define a Gaussian curve.
The function with the highest value for x=minimum daily measured ice extent (from the lowest daily 2009 value from IARC-JAXA) wins.
As of 21 July, the sea ice extent was 7,848 thousand km2.
When mapping a moderately weathered area, it is important to keep in mind that preservation-based selection effects may strongly bias the observable outcrop. Figure 1 shows some dolomite subcrop (with a silicified stromatolite) in red soil. 
Figure 1. Dolomite subcrop with silicified stromatolite. Hammer for scale.
Since dolomite (plus or minus alteration) is the only rock that crops out in this area, it would be tempting to map the area as dolomite. However, as this historical digging shows (figure 2), the rock in the area actually consists of interlayered dolomite, shale, and dololutite. But the shale and dololutite are friable, so it is only the hard, massive dolomites (or silicified fossils) that are present in natural outcrop. 
Figure 2. Historical diggings showing actual stratigraphy. Massive dolomite is confined to thin layers, and the dominant rock is shale and dololutite. Lizard for scale.
Chris and Sheril have a new book out on scientific failures to communicate. I haven't read it, as it was not available in my local bookstore here in Oz. Fortunately, here in blog land, my failure to even see the book qualifies me to review it. From what I'm told, the late Carl Sagan is used as an example of a great science communicator. Trouble is, my local bookstore didn't have any of his books either. Lomborg and Plimer, yes, but no Mooney or Carl.
A lot of scientists enthusiastically cite Sagan as one of the inspirations for their careers. And that is fine. But here's the thing. Sagan was a great preacher, sure. But for the most part, he preached to the choir. Welders and car dealers aren't nearly as excited about him as astronomers are. So when it comes to finding a way to bridge the gap between science and the technophopic world, he is probably not the best example. In fact, I'm not really sure who is. but I reckon that the late Steve Irwin would be in the running.
I am far from a perfect geologist. One of my most annoying habits, both to my self later on and to my colleagues, is that I often forget to put a scale bar in my field photos. Obviously not knowing the size of various features results in substantial information loss, so this is something that I tried to specifically address during our 2008 field season.
The one item that we don’t leave the truck without is a GPS. For one thing, all data has to be tied to a location point- there’s no point taking a picture of the biggest gold nugget evah if we don’t know where it is. And secondly, in areas on subdued topography, incomplete drainage, and/or thick scrub, the GPS is the best tool for finding one’s way back to the vehicle. So, I decided that the obvious thing to do was to add a scalebar to my receiver. Here’s the result.
Figure 1. slickensides and veining in sandstone. GPS gradations are centemeters.
Do any of y’all have geologic habits bad enough to necessitate the use of pink paint markers?
p.s. Kim, Sinistral?
My PhD work involved fieldwork in East-central Brazil. After about a year of correspondence with a geologist at the Bahia state survey who was an expert on the stratigraphy, the plan was for me to accompany him into the field. As someone who had worked in the area for decades, he was in charge of the logistics, while I, the student from the top notch analytical school, was in charge of all geochemical and geochronological analyses.
That was the plan.
My flight into Salvador arrived at 12:30 am. When my collaborator met me at the airport, he informed me that he would no longer be taking part in the project, and that I was basically on my own. That I eventually managed to get samples and results (the writing up of which is the reason this blog is on autopilot) was a miracle. But it was pure luck that I didn’t end up like these guys.
For those of you who don’t read All my Faults are Stress Related, or Arizona Geology, five students, three American and two Brazilian, were recently arrested for geological sampling without the proper paperwork. The Americans are required to stay in Brazil until legal proceedings are finished.
Brazil is a country with complicated bureaucracy and spastic enforcement. Unlike these guys, I had a proper multiple entry business visa, as I was going to Guyana for a related project before starting my fieldwork. Upon my return, the border guard slashed the expiry date on my visa by two months, to the day BEFORE my outgoing flight, just because he was cranky his soccer team was losing on the television. Had a similar cop asked why the guy named in our permits was 400 km away from the sample site, I would have been in an even worse situation than these folks. So please spare a thought for people caught in a system where, even if you do manage to navigate the Byzantine labyrinth of regulations, sadistically capricious enforcement can still screw you over.
Role playing time, lemminglets. Suppose you are reviewing a paper. Also assume, that like most papers these days, that it has multiple authors, each of whom applies his expertise to the problem at had. And finally, assume that you are an expert in some, but not all of the fields used to solve the particular problem being reported in this paper.
What do you do if one of the key points in the paper that is not your area of expertise seems fishy. For example, if the paper is on your field area, what if some of the lab results seem fishy. Or if you are an analyst, what if the experimental setup seems odd.
Assuming that you are a successful researcher, you probably have long-time collaborators who are experts in these fields. So, what is the best way of accessing their expertise, given that some sort of confidence generally surrounds papers in review.
By ‘best’ I mean best for science, but if any of y’all want to interpret this as ‘best for me’ or ‘best for the editor’ or ‘best for the author’, that is fine too.
With 4 weeks left to guess, the graph for the 2009 Arctic sea ice minimum gaussian guessing game is looking like this:
Contestants have solid, colored curves. The thick black/grey curves are the Ensemble 1 and 2 outputs from the Wegener Institute’s June 2009 Sea Ice outlook. The collective contestant’s pdf is the dotted light grey line (click to embiggen). It has grown from a bimodal distribution around the 2007 and 2008 minima, to a trimodal distribution with a third peak around 4000. Nick Barnes (4700 ± 200, pink) still needs to take another guess, if he so desires.
The current value (as of Friday) is 9,500 thousand km2.
It's time to celebrate freedom from despotic tyrants, pyrotechnics, and BBQ. The first two aren't really big here in Australia, but the following suppliment to the third category makes up for all that.
BBQ sauce. Made from beer. What more could you want?
A few months back, I blogged about the client with a spam filter so tight that it embargoed emails about single young zircon dating. After conferring with said clients, it turns out that they’ve had other issues as well. In its animatronic zeal to rid the internet of pornography, this filter also blocks image files that it suspects are explicit. What sort of images? Well, anything containing a lot of pink, as it turns out. So, rose quartz, rhodocrosite, Mg-rich garnets, and other titillating mineral images have been known to disappear into the computer program’s private locker. Luckily they ship geologic maps as GIS files instead of images, or I’m sure they’d be targeted as well.
This got me thinking. How common are explicit geologic formations? You’d think that will all the zillions of folded, rounded, curved, or protruding structures on this planet, at least a few would be shaped like something that would constrict the coronary arteries of a shrill old censor. So, this is my challenge to the blogosphere: Find juiciest, most risqué geologic image that you feel comfortable posting, and put it out on the internet. Your traffic in tragically maladjusted lapidarians will expand tremendously, I guarantee.
Sadly, all I can offer in this department is this backscattered electron image of a rutile. To most people, it is simple igneous compositional zoning of Nb, Sn and W, which reflect electrons more efficiently than titanium and therefore appear bright. But to the dirty regolithic mind, this only needs legs, arms, and a head to become a swimsuit model. And no, I don’t need to leave the lab more often.
Figure 1. Detrital Phanerozoic rutile believed to be of pegmatitic origin See Birch et al. 2007 for geochronology and trace element characteristics.
