# Tag Archives: Science

## Weighing Scientists

The latest (top science journal) Nature has an editorial on the need for better ways to communicate expert uncertainty on key topics like climate change, and a two-pager by Willy Aspinall on “More tractable expert advice“:

Of the many ways of gathering advice from experts, the Cooke method is, in my view, the most effective when data are sparse, unreliable or unobtainable. … Take as an example an elicitation I conducted in 2003, to estimate the strength of the thousands of small, old earth dams in the United Kingdom. Acting as facilitator, I first organized a discussion between a group of selected experts. … The experts were then asked individually to give their own opinion of the time-to-failure in a specific type of dam, once such leakage starts. They answered with both a best estimate and a ‘credible interval’, for which they thought there was only a 10% chance that the true answer was higher or lower. Continue reading "Weighing Scientists" »

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## Real Science

Fascinating observations from watching real science in action.  Half of data conflicts with theoretical expectations:

Although the researchers were mostly using established techniques, more than 50 percent of their data was unexpected. (In some labs, the figure exceeded 75 percent.) … “The results kept contradicting their theories. It wasn’t uncommon for someone to spend a month on a project and then just discard all their data because the data didn’t make sense.” …

There were models that didn’t work and data that couldn’t be replicated and simple studies riddled with anomalies. “These weren’t sloppy people,” Dunbar says. “They were working in some of the finest labs in the world. But experiments rarely tell us what we think they’re going to tell us. That’s the dirty secret of science.” …

Most such anomalies are just ignored:

The vast majority of people in the lab followed the same basic strategy. First, they would blame the method. The surprising finding was classified as a mere mistake; perhaps a machine malfunctioned or an enzyme had gone stale. … The experiment would then be carefully repeated. Sometimes, the weird blip would disappear, in which case the problem was solved. But the weirdness usually remained, an anomaly that wouldn’t go away.  …

Even after scientists had generated their “error” multiple times — it was a consistent inconsistency — they might fail to follow it up. “Given the amount of unexpected data in science, it’s just not feasible to pursue everything.” …

Marginalized folks contribute more to innovation:

Thorstein Veblen was commissioned … to write an essay on how Jewish “intellectual productivity” would be changed if Jews were given a homeland. … [he] argued instead that the scientific achievements of Jews — at the time, Albert Einstein was about to win the Nobel Prize and Sigmund Freud was a best-selling author — were due largely to their marginal status.  … They were able to question everything, even the most cherished of assumptions. …

Diversity induces far view talk, which finds creative answers:

The diverse lab, in contrast, mulled the problem at a group meeting. None of the scientists were protein experts, so they began a wide-ranging discussion of possible solutions. …. “After another 10 minutes of talking, the protein problem was solved.” .. The intellectual mix generated a distinct type of interaction in which the scientists were forced to rely on metaphors and analogies to express themselves. … These abstractions proved essential for problem-solving, as they encouraged the scientists to reconsider their assumptions. Having to explain the problem to someone else forced them to think, if only for a moment, like an intellectual on the margins, filled with self-skepticism.

Thorstein Veblen is under-appreciated, as is how weak are our theories.  How much innovation do we lose because Jews are no longer on the margin?  Hat tip to R0bert Koslover.

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## Random Smoking Trials

Hal Finney recently commented:

[Johnstone & Finch’s] Scientific Scandal of Antismoking … makes the case that smoking is not bad for your health. … [It has] the superficial appearance of referencing scientific studies and claiming the the mainstream misrepresents the results.

Yes, they are superficially credible.  Their New Scientist letter:

WHO … claims … “an epidemic of chronic illnesses … could be prevented through simple changes in diet, by being more active and by not smoking.” … There have been a number of such studies, with various combinations of these three lifestyle factors, including the WHO collaborative trial (60,881 subjects, 6 years), the Goteborg trial (30,022 subjects, 11.8 years) and the Multiple Risk Factor Intervention trial (12,866 subjects, 7 years).  These and another eight trials were conducted over three decades, one of the most expensive and sustained series of biological experiments in the history of medical science. … None showed any improvement in life expectancy and two showed a significant reduction in life expectancy in the test group.

So I dug further; bottom line:  Johnstone & Finch are right.  We usually see strong correlations between death and smoking, and we see those same correlations within each random arm (i.e., group) of a randomized trial.  Nevertheless, we see no significant net death differences between control arms and arms induced to smoke less.

So we don’t have clear evidence that smoking kills on net; it could be that most or all of the death-smoking correlation is due to selection effects, and not smoking causing death.  Experts say there is a substantial causal component, and for now I’m accepting that claim, but this lack of clear evidence is suspicious, and disturbing.  Now for some details. Continue reading "Random Smoking Trials" »

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## All Hail William Napier

William Napier was born in 1940 and got his Ph.D. three years after his B.S., in 1966.   After a career as a professional astronomer, he published his first book of fiction in 1998, at the age of 58, and published three more over the next five years.

But I still would not have heard of Napier had I not read his two brilliant 2007 Astrobiology papers, published when he was 67.  The first argued comets were a likely origin of life:

A single comet of radius 10 km … contains [about] as much clay … as … early Earth. … Our Solar System is surrounded by about 1011 comets … A cometary interior provides a stable, aqueous, organic-rich environment for around 106 years.

The second showed that life could spread across a galaxy when via giant molecular clouds reliably collecting life from the stars they drift near, and then passing that life on to a few of the thousands of new stars they create.  I now honor Napier by quoting lots of his detail: Continue reading "All Hail William Napier" »

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## A Galactic Garden

In August I wrote:

A few years ago PCW Davies persuasively argued that Earth life more likely started on Mars.  Last year, Napier and coauthors argued that comets are an even more likely source:

A single comet of radius 10 km and 30% volume fraction of clay contains as much clay, to within a factor of around 10, as that of the early Earth. However, our Solar System is surrounded by about 1011 comets forming the Oort cloud …  Whereas the average persistence of shallow clay pools and hydrothermal vent concentrations of clay on the Earth can range from 1 to around 100 years, a cometary interior provides a stable, aqueous, organic-rich environment for around 106 years.

The larger the region from which life could plausibly have started and then come to Earth, the more likely Earth life becomes in that scenario, and the more believable is whatever theory suggested that scenario.  The latest Scientific American suggests to me an even larger plausible region of orgin: life’s origin may go back to the tight warm mixing cluster of stars where the Sun formed.  Simon Zwart: Continue reading "A Galactic Garden" »

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## There Is No Science

I like listening to journalists talk about science … most of the translation to outsiders comes from non-scientists simply because there are more of them, and some write very well.  Yet, I find many times, when these journalists digress from a specific subject, to science in general they are extremely naive or duplicitous. If you go to The Skeptic’s Guide to the Universe, you invariably hear a bunch of caricatures of those who disagree with conventional wisdom on science—most of which truly are quacks, but not always—and they pedantically emphasize how these alternative views are ‘not science’: they have beliefs that do not have peer-reviewed tests supporting a falsifiable hypothesis. …

When journalists talk about science in general this is usually a pretext for saying those who disagree with their favorite idea are wrong, because they are unscientific. … They then caricature their opponents, taking the most inarticulate advocates from the other side, and skewering their illogic. They then sit back and take take inordinate pride in their scientific pretensions, as if their selective discussion was objective. The fact is, most ‘big’ scientific issues do not conform to the scientific method, where one puts out testable hypotheses, rejecting ones that are falsified.

He’s right: “science” basically means “study”, and there just is no simple way for outsiders to tell who is studying something well.  The best way to study a subject depends a lot on the details of that subject.  We have a few rough guides to expertise, such as careful language, formalism, attention to detail, years of study, IQ, cleanliness, endorsement by respected folks, etc., but there is no surefire ‘science’ checklist that can tell outsiders if research is good.

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## Words Vs. Bets

I once had a long discussion with Ken Steiglitz about P=NP, while I was still at Princeton. … Ken was and still is sure that P must not be equal to NP. Okay, I said to Ken, what are the odds that they are equal? Ken said that he thought the odds were a million to one. I immediately suggested a bet. I did not ask him to “bet his life,” but I did ask for a million to one bet. I would put up one dollar. If in say ten years P=NP had not been proved, then he would win my dollar. If P=NP was proved in that time frame, then I would win a million dollars from Ken. Ken said no way. After more discussion the best bet I could get out of Ken was ${2}$ to ${1}$.  Two to one. That was the best he would do.

That is from Richard Lipton; hat tip to Michael Nielsen.  Does anyone doubt that two to one better summarizes his evidence than a million to one?

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## Just Beautiful

Don’t miss the hi-res version.

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## Why Does Pharma Study Placebos?

As head of Lilly’s early-stage psychiatric drug development in the late ’90s, Potter saw that … the company’s next-generation antidepressants were faring badly, too, doing no better than placebo in seven out of 10 trials. … Potter discovered, however, that geographic location alone could determine whether a drug bested placebo or crossed the futility boundary. By the late ’90s, for example, the classic antianxiety drug diazepam (also known as Valium) was still beating placebo in France and Belgium. But when the drug was tested in the US, it was likely to fail. Conversely, Prozac performed better in America than it did in western Europe and South Africa. It was an unsettling prospect: FDA approval could hinge on where the company chose to conduct a trial. …

AsPotter and his colleagues [also] discovered that ratings by trial observers varied significantly from one testing site to another. It was like finding out that the judges in a tight race each had a different idea about the placement of the finish line. … The placebo response is highly sensitive to cultural differences. Anthropologist Daniel Moerman found that Germans are high placebo reactors in trials of ulcer drugs but low in trials of drugs for hypertension—an undertreated condition in Germany, where many people pop pills for herzinsuffizienz, or low blood pressure. Moreover, a pill’s shape, size, branding, and price all influence its effects on the body. Soothing blue capsules make more effective tranquilizers than angry red ones, except among Italian men, for whom the color blue is associated with their national soccer team—Forza Azzurri! …

AsIn the spring, Potter, who is now a VP at Merck, helped rev up a massive data-gathering effort called the Placebo Response Drug Trials Survey.  Under the auspices of the NIH, Potter and his colleagues are acquiring decades of trial data—including blood and DNA samples—to determine which variables are responsible for the apparent rise in the placebo effect. Merck, Lilly, Pfizer, AstraZeneca, GlaxoSmithKline, Sanofi-Aventis, Johnson & Johnson, and other major firms are funding the study, and the process of scrubbing volunteers’ names and other personal information from the database is about to begin.  In typically secretive industry fashion, the existence of the project itself is being kept under wraps. NIH staffers are willing to talk about it only anonymously, concerned about offending the companies paying for it.

More here.  Gee, do you think drug companies will use their better understanding of placebo effects to help us all better distinguish effective from useless drugs, or do you think they will instead use it to game the FDA approval process, to make more of their drugs look better than placebos?  What do these two theories predict about how secretive they would be about such research?

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## CO2 Warming Looks Real

Many have bent my ear over the last few months about global warming skepticism.   So I’ve just done some moderate digging, and conclude:

1. In the last half billion years, CO2 has at times been 15 times denser, but not more than 10C warmer.  So that is about as bad as warming could get.
2. In the last million years, CO2 usually rises after warming; clearly warming often causes CO2 increases.
3. CO2 is clearly way up (~30%) over 150 years, and rising fast, mainly due to human emissions.  CO2 is denser than its been for a half million years.
4. The direct warming effect of CO2 on warming is mild and saturating; the effects of concern are indirect, e.g., water vapor and clouds, but the magnitude and sign of these indirect effects are far from clear.
5. Climate model builders make indirect effect assumptions, but most observers are skeptical they’ve got them right.
6. This uncertainty alone justifies substantial CO2 mitigation (emission cuts or geoengineering), if we are risk-averse enough and if mitigation risks are weaker.
7. Standard warming records show a real and accelerating rise, roughly matching the CO2 rise.
8. Such warming episodes seem common in recent history.
9. The match between recent warming and CO2 rise details is surprisingly close, substantially raising confidence that CO2 is the main cause of recent warming.  (See this great analysis by Pablo Verdes.)  This adds support for mitigation.
10. Among the few bets on global warming, the consensus is for more warming.
11. Geoengineering looks far more likely to be feasible and acceptable mitigation than emissions cuts.
12. Some doubt standard warming records, saying they are biased by urban measuring sites and arbitrary satellite record corrections.   Temperature proxies like tree rings diverge from standard records in the last fifty years. I don’t have time to dig into these disputes, so for now I defer to the usual authorities.

It was mostly skeptics bending my ear, and skeptical arguments are easier to find on the web.  But for now, the other side has convinced me.

Added: The Verdes papers is also here.  Here is his key figure: Continue reading "CO2 Warming Looks Real" »

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