Tag: science

The second neutrino experiment appears to confirm the previous result:

One of the most staggering results in physics – that neutrinos may go faster than light – has not gone away with two further weeks of observations. The researchers behind the jaw-dropping finding are now confident enough in the result that they are submitting it to a peer-reviewed journal.

“The measurement seems robust,” says Luca Stanco of the National Institute of Nuclear Physics in Padua, Italy. “We have received many criticisms, and most of them have been washed out.”

Stanco is a member of the OPERA collaboration, which shocked the world in September with the announcement that the ghostly subatomic particles had arrived at the Gran Sasso mine in Italy about 60 nanoseconds faster than light speed from the CERN particle accelerator near Geneva, Switzerland, 730 kilometres away. Theorists have been struggling to reconcile the September result with the laws of physics. Einstein’s theory of special relativity posits that nothing can travel faster than light, and many physicists believe the result could disappear in a puff of particles.

The result also unsettled those within the OPERA collaboration. Stanco was one of 15 team members who did not sign the original preprint of the paper because they thought the results were too preliminary.

One of the main concerns was that it was difficult to link individual neutrino hits at Gran Sasso to the particles that left CERN. To double check, the team ran a second set of measurements with tighter bunches of particles from 21 October to 6 November.

In that time, they observed 20 new neutrino hits – a piddling number compared with the 16,000 hits in the original experiment. But Stanco says the tighter particle bunches made those hits easier to track and time: “So they are very powerful, these 20 events.”
More checks

The team also rechecked their statistical analysis, confirming that the error on their measurements was indeed 10 nanoseconds. Some team members, including Stanco, had worried that the true error was larger. What they found was “absolutely compatible” with the original announcement, he says.

Fascinating stuff. It’s tremendously amusing to see all the physicists pooh-poohing the reports and producing literally dozens of why what has reportedly happened couldn’t possibly have happened. It would appear supraluminal neutrinos are the Tim Tebow of the physics world. Anyhow, if there are subsequent confirmations of faster-than-light speed and the scientific consensus of the physics world mutates once more, I have little doubt that the atheists of the future will be one day be arguing that the Bible is wrong because it implies nothing can move faster than light. They’ve done this with both Ptolemy’s geocentric theory and the Flat Earth theory, so there is no reason to believe they won’t eventually blame Einstein’s mistakes on God as well.

The experiments also serve to substantiate my critique of the “extraordinary claims” argument. Traveling faster than light is every bit as extraordinary a claim as the existence of the supernatural; it is actually more extraordinary because claims are far less frequently made for it. And yet, the experiment has been repeated once, will be peer reviewed, and will probably be replicated once or twice in the relatively near future.

If this is “extraordinary evidence”, then science is in much worse shape than either the science critics or the science fetishists imagine.

But let’s not forget the most important factor here: supraluminal speed is just cool.

And neither are many other pseudoscientific fields with scientific pretensions. Because the credibility of science depends upon its replicability, it naturally follows that any “scientist” who does not release his data for independent review and replication is not doing science:

In a recent survey, two-thirds of Dutch research psychologists said they did not make their raw data available for other researchers to see.

Then they are witch-doctors, propagandists, and grant-seekers, not scientists. Some years ago, I wrote about the need for Open Science. But the more that I think about it, that is redundant. Because if it isn’t open, it isn’t science. To paraphrase the OpenScience Project, if you’re going to do science, you have to release the computer code too.

“Our view is that it is not healthy for scientific papers to be supported by computations that cannot be reproduced except by a few employees at a commercial software developer. Should this kind of work even be considered Science? It may be research, and it may be important, but unless enough details of the experimental methodology are made available so that it can be subjected to true reproducibility tests by skeptics, it isn’t Science.”

This was also amusing to note in light of my contention that most scientists are completely untrained in statistics.

“Also common is a self-serving statistical sloppiness. In an analysis published this year, Dr. Wicherts and Marjan Bakker, also at the University of Amsterdam, searched a random sample of 281 psychology papers for statistical errors. They found that about half of the papers in high-end journals contained some statistical error.”

The fundamental flaw in the common, but erroneous idea that science is an intrinsically superior form of obtaining knowledge is that it relies upon the same human element that various other forms of knowledge do. Notice that the amount of detected scientific fraud appears to be increasing as electronic communications provide greater access to non-scientists, and that even in this case, where the whistleblowing was done by scientists, it was not done as part of the scientific process.

Diederik Stapel was suspended from his position at Tilburg University in the Netherlands in September after three junior researchers reported that they suspected scientific misconduct in a study that claimed eating meat made people more aggressive. Soon after being confronted with the accusations, Stapel reportedly told university officials that some of his papers contained falsified data. The university launched an investigation, as did the University of Groningen and the University of Amsterdam, where Stapel had worked previously. The Tilburg commission today released an interim report (in Dutch), which includes preliminary results from all three investigations. The investigators found “several dozens of publications” in which fictitious data has been used. Fourteen of the 21 Ph.D. theses Stapel supervised are also tainted, the committee concluded.

Stapel issued a statement today in which he apologizes to his colleagues and says he “failed as a scientist” and is ashamed of his actions. He has cooperated to an extent by identifying papers with suspect data, according to university officials. The investigation by the three universities is ongoing and should ultimately investigate more than 150 papers that Stapel has published since 2004, including a paper earlier this year in Science on the influence of a messy environment on prejudice. “People are in shock,” says Gerben van Kleef, a social psychologist at the University of Amsterdam, who did not work directly with Stapel. “Everybody wonders how this could have happened and at this proportion.”

Stapel’s work encompassed a broad range of attention-catching topics, including the influence of power on moral thinking and the reaction of psychologists to a plagiarism scandal. The committee, which interviewed dozens of Stapel’s former students, postdoctoral researchers, co-authors, and colleagues, found that Stapel alone was responsible for the fraud. The panel reported that he would discuss in detail experimental designs, including drafting questionnaires, and would then claim to conduct the experiments at high schools and universities with which he had special arrangements. The experiments, however, never took place, the universities concluded. Stapel made up the data sets, which he then gave the student or collaborator for analysis, investigators allege. In other instances, the report says, he told colleagues that he had an old data set lying around that he hadn’t yet had a chance to analyze. When Stapel did conduct actual experiments, the committee found evidence that he manipulated the results.

Many of Stapel’s students graduated without having ever run an experiment, the report says. Stapel told them that their time was better spent analyzing data and writing. The commission writes that Stapel was “lord of the data” in his collaborations. It says colleagues or students who asked to see raw data were given excuses or even threatened and insulted.

Now, keep in mind that science fetishists often claim that science is intrinsically superior because scientific evidence theoretically can be replicated. But this argument is fundamentally flawed; no one argues that eyewitness testimony that theoretically could be confirmed by physical evidence is intrinsically superior to eyewitness evidence that cannot be independently confirmed in the absence of actually bothering to verify the testimony.

Clearly, a bright line needs to be delineated between scientific evidence that has been independently replicated by experiment, scientific evidence that could be independently replicated but has not been, and scientific evidence that cannot be independently replicated by experiment. And furthermore, it is necessary to stop giving the latter two types of scientific evidence, or more properly, potential scientific evidence, the same level of credence that is given to actual scientific evidence that has been reliably and independently replicated.

This critique of economic models might be helpful in explaining why I am so strongly skeptical about TE(p)NSBMGDaGF as well as the various dating methodologies. As I have mentioned on several occasions before, scientists in many fields simply don’t realize that the conceptual tools they utilize on a regular basis are significantly less reliable than they assume. The foundations upon which their “evidence” rests is much shakier than they understand, for the most part. This is understandable, since very few biologists, geologists, or astronomers have any actual training in history, logic, statistics, probability, higher mathematics, or even spreadsheet use, but that doesn’t excuse their stubborn and willful ignorance when errors, or even the likelihood of errors, based on these factors are pointed out to them.

Carter had initially used arbitrary parameters in his perfect model to generate perfect data, but now, in order to assess his model in a realistic way, he threw those parameters out and used standard calibration techniques to match his perfect model to his perfect data. It was supposed to be a formality–he assumed, reasonably, that the process would simply produce the same parameters that had been used to produce the data in the first place. But it didn’t. It turned out that there were many different sets of parameters that seemed to fit the historical data. And that made sense, he realized–given a mathematical expression with many terms and parameters in it, and thus many different ways to add up to the same single result, you’d expect there to be different ways to tweak the parameters so that they can produce similar sets of data over some limited time period.

The problem, of course, is that while these different versions of the model might all match the historical data, they would in general generate different predictions going forward–and sure enough, his calibrated model produced terrible predictions compared to the “reality” originally generated by the perfect model. Calibration–a standard procedure used by all modelers in all fields, including finance–had rendered a perfect model seriously flawed. Though taken aback, he continued his study, and found that having even tiny flaws in the model or the historical data made the situation far worse. “As far as I can tell, you’d have exactly the same situation with any model that has to be calibrated,” says Carter.

I first realized the nature of the problem when a perfectly straightforward question about the average speed of the evolutionary process was not so much mocked as greeted with complete confusion. And yet, if a process has taken place more than once over time, logic requires that there must be both various measurable speeds as well as an average speed. It doesn’t matter if the process measured is from mutated state to mutated state or from species to species, there must be an answer if the process is occurring. It wasn’t the lack of an answer that was the red flag, but rather, the inability to understand that there absolutely had to be an answer even if the answer was unknown at the present time.

The calibration problem that Carter is pointing out is tangentially related to the “backdating” problem I have hitherto observed. Economists and finance guys are keenly aware of the precarious nature of their models because they are forced to see them tested rigorously in real-time. For example, the administration economists who estimated a 1.6 multiplier effect in 2008 already know they were wrong. (They may not find it politically feasible to openly admit this, but they definitely know it, which is why they’re not proposing another stimulus package on the same basis.) And investment models blow up literally all the time, sometimes in a spectacular, system-threatening manner.

But that same sort of performance pressure simply doesn’t exist in many of the various sciences that concern past events. This is why we can be confident, if not entirely certain, that in the absence of successful predictive models, they have gotten it so substantially wrong that their core concepts will not survive the eventual corrections when they finally arrive.

To give another example, if evolution were a real science, biologists would be able to predict what the next species to evolve would be, as well as which population groups within a species were more evolved than the norm. They would be able to discern the connection between race and evolutionary development in humans. In fact, given the pressure that human activity is putting on various environments, we should be seeing more and more species evolving every more rapidly in comparison with the more sedate natural changes in various environments over the years. But that does not appear to be the case.

And appeals to time don’t wash either. Homo sapiens sapiens is supposed to have evolved to full modernity 50,000 years AGO, a process that is said to have taken 150,000 years. But since there are 59,811 species of vertebrates, even if we assume that the complex human evolution is the norm, we should be seeing a new vertebrate species evolve once every 2.5 years, (and a new mammal species every 27.3 years) even without the increased selection pressure of human habitat modification.

Now, there have been a number of new mammalian species, mostly lemurs and monkeys, discovered since 2000. So, perhaps there is some evidence for this process, if any of those species can be determined to be newly evolved rather than merely previously undiscovered. But the observable fact remains that evolutionary biologists, and many other scientists in other fields, simply don’t even think in a systematic manner that would allow them to perceive the logical holes in their fundamental models.

How dare he!

Lots of “scientific evidence” goes wrong.

Point and screech, boys. I’ll be very disappointed in you if you don’t point and screech.

Some scientists really seem quixotically determined to convince the masses that it is in the best interests of humanity to turn scientist-hunting into a sport:

The bacterium that causes plague, Yersinia pestis, is still highly virulent today but has somewhat different symptoms, leading some historians to doubt that it was the agent of the Black Death.

Those doubts were laid to rest last year by detection of the bacterium’s DNA in plague victims. With the full genome now in hand, the researchers hope to recreate the microbe itself so as to understand what made the Black Death outbreak so deadly.

Full credit to science for nearly eliminating smallpox and polio. And I’m sure we all support the efforts to rid the world of cancer. But recreating the Black Death virus seems like an epically stupid idea. Of course, a member of the team says “the ancient plague would presumably be susceptible to antibiotics”. Presumably. That’s confidence-inspiring. The universities of the West should really consider making a semester in basic risk/benefit analysis a mandatory requirement for any science major.

Besides, if scientists are going to recreate something, i think they should bring back the dire wolf and the sabertooth tiger. Those would be cool and neither used to kill millions of people at a time.

The materialist argument against testimonial evidence is that it relies heavily on the truthfulness of the witness. The great irony is that this is also true of science as it is actually practiced, as opposed to that imaginary ideal science in which every experimental result is duly replicated multiple times. The Economist describes an episode of scientific misconduct that reveals how most of what passes for science today holds no claim to even being called science, let alone possesses any scientific authority.

ANIL POTTI, Joseph Nevins and their colleagues at Duke University in Durham, North Carolina, garnered widespread attention in 2006. They reported in the New England Journal of Medicine that they could predict the course of a patient’s lung cancer using devices called expression arrays, which log the activity patterns of thousands of genes in a sample of tissue as a colourful picture (see above). A few months later, they wrote in Nature Medicine that they had developed a similar technique which used gene expression in laboratory cultures of cancer cells, known as cell lines, to predict which chemotherapy would be most effective for an individual patient suffering from lung, breast or ovarian cancer.

At the time, this work looked like a tremendous advance for personalised medicine—the idea that understanding the molecular specifics of an individual’s illness will lead to a tailored treatment. The papers drew adulation from other workers in the field, and many newspapers, including this one (see article), wrote about them. The team then started to organise a set of clinical trials of personalised treatments for lung and breast cancer. Unbeknown to most people in the field, however, within a few weeks of the publication of the Nature Medicine paper a group of biostatisticians at the MD Anderson Cancer Centre in Houston, led by Keith Baggerly and Kevin Coombes, had begun to find serious flaws in the work….

Finally, in July 2010, matters unravelled when the Cancer Letter reported that Dr Potti had lied in numerous documents and grant applications. He falsely claimed to have been a Rhodes Scholar in Australia (a curious claim in any case, since Rhodes scholars only attend Oxford University). Dr Baggerly’s observation at the time was, “I find it ironic that we have been yelling for three years about the science, which has the potential to be very damaging to patients, but that was not what has started things rolling.”…

The process of peer review relies (as it always has done) on the goodwill of workers in the field, who have jobs of their own and frequently cannot spend the time needed to check other people’s papers in a suitably thorough manner.

Now, there are two significant points here. First, the reason the hypothesis was eventually falsified wasn’t due to the scientific method, but because of historical documentary evidence, namely, the false claim of Dr. Potti to have been a Rhodes Scholar in Australia. Second, most “science” is not only never experimentally replicated, but the unscientific editing process known as peer review isn’t even performed properly in most cases.

When comparing science and other forms of knowledge, it is not logically consistent to compare ideal science versus the practical real world application of those alternatives. Either ideal science can be compared to ideal alternatives or actual science can be compared to actual alternatives. It is as nonsensical to claim that all reported science is reliable as it would be to claim that all historical documents are accurate and all eyewitness testimony is true.

Just as some eyewitness testimony is false and some historical documents are inaccurate, most scientific reports are neither properly peer-reviewed nor replicated in any manner. Therefore, no scientific paper can credibly claim the authority of science until it has been demonstrated that it has been both properly peer-reviewed and duly replicated.