However good data looks at first sight, check it!

Introduction

I will tell today two true stories, one old and one very recent. The point that I want to make today is that one should never blindly trust the results of measurements. This applies in general, but both examples I will present have to do with measurements made with instruments, more specifically with measuring UV-B radiation in experiments using lamps.

A case from nearly 20 years ago

Researcher A received a new very good spectroradiometer from the manufacturer and used it to set the UVB output from the lamps.

Researcher B had access to an old spectroradiometer that could measure only a part of the UVB spectrum. He knew this, and measured the part of the spectrum that was possible to measure, and extrapolated the missing part from published data. He also searched the literature and compared his estimates to how the same lamps had been used earlier.

Researcher A was unlucky enough that because of a mistake at the factory, the calibration of the new instrument was wrong by about a factor of 10. She did not notice until after the experiment was well under way, but before publication. The harm was that the results were less relevant than what had been the aim, but no erroneous information was published.

Researcher B was able able to properly measure the UVB irradiance after the experiment was well under way, and he found that the treatment was within a small margin of what he had aimed.

A case I discovered just a few days ago

A recently published paper concluded that they had obtained evidence that a low and ecologically relevant dose of UVB on a single day was able to elicit a large response in the plants. From the description of the lamps used, the distance to the plants and the time that the lamps were kept switched on is easy to estimate that in fact they had applied a dose that was at least 15 or 20 times what they had measured and reported in the paper. Coupled to a low level of visible light this explains why they observed a large response from the plants! Neither the authors, reviewers, nor the editor had noticed the error! [added on 8 October] I read a few other papers on similar subjects from the same research group and the same problem seems to also affect them. I will try to find out the origin of the discrepancy, and report here what I discover.

[added on 26 October]
I have contacted three of the authors. They have confirmed the problem. Cause seems to have been that the researchers did not notice that the calibration they used had been expressed in unusual units by the manufacturer. The authors are concerned and are checking how large the error was, but first comparative measurements suggest that the reported values were underestimated by a factor of at least 20 times.

About this case, I do not yet know the whole story, but evidently it yielded a much worse result: The publication of several articles with wrong data and wrong conclusions.

Take home message

Whenever and whatever you measure, or when you use or assess non-validated data from any source, unless you know very well from experience what to expect, check the literature for ballpark numbers. In either case, if your data differ significantly from expectations try to find an explanation for the difference before you accept the data as good. You will either find an error or discover something new.

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