Multivariate optical computing

Article summary

Multivariate optical computing, also known as molecular factor computing, is an approach to the development of compressed sensing spectroscopic instruments, particularly for industrial applications such as process analytical support. "Conventional" spectroscopic methods often employ multivariate and chemometric methods, such as multivariate calibration, pattern recognition, and classification, to extract analytical information (including concentration) from data collected at many different wavelengths. Multivariate optical computing uses an optical computer to analyze the data as it is collected. The goal of this approach is to produce instruments which are simple and rugged, yet retain the benefits of multivariate techniques for the accuracy and precision of the result. An instrument which implements this approach may be described as a multivariate optical computer. Since it describes an approach, rather than any specific wavelength range, multivariate optical computers may be built using a variety of different instruments (including Fourier Transform Infrared (FTIR) and Raman ).…

Key claims

1. publication date: 1997 — source: Wikipedia · confidence 0.95
2. publication date: 2012 — source: Wikipedia · confidence 0.95

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1. Summarise the article in your own words. Which single claim would you verify first, and why?
2. The record states that the publication date is "1997". What evidence would count against this claim?
3. The record states that the publication date is "2012". What evidence would count against this claim?
4. Which claim in this article is most likely to be revised as the sources update? How would you check its current status?
5. If two sources disagreed about one of these facts, what would you need in order to trust one over the other?

Bibliography

1. Wikipedia https://en.wikipedia.org/w/index.php?oldid=1373949824