Publications

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2014
Paterson, GA, Tauxe L, Biggin AJ, Shaar R, Jonestrask LC.  2014.  On improving the selection of Thellier-type paleointensity data. Geochemistry Geophysics Geosystems. 15:1180-1192.   10.1002/2013gc005135   AbstractWebsite

The selection of paleointensity data is a challenging, but essential step for establishing data reliability. There is, however, no consensus as to how best to quantify paleointensity data and which data selection processes are most effective. To address these issues, we begin to lay the foundations for a more unified and theoretically justified approach to the selection of paleointensity data. We present a new compilation of standard definitions for paleointensity statistics to help remove ambiguities in their calculation. We also compile the largest-to-date data set of raw paleointensity data from historical locations and laboratory control experiments with which to test the effectiveness of commonly used sets of selection criteria. Although most currently used criteria are capable of increasing the proportion of accurate results accepted, criteria that are better at excluding inaccurate results tend to perform poorly at including accurate results and vice versa. In the extreme case, one widely used set of criteria, which is used by default in the ThellierTool software (v4.22), excludes so many accurate results that it is often statistically indistinguishable from randomly selecting data. We demonstrate that, when modified according to recent single domain paleointensity predictions, criteria sets that are no better than a random selector can produce statistically significant increases in the acceptance of accurate results and represent effective selection criteria. The use of such theoretically derived modifications places the selection of paleointensity data on a more justifiable theoretical foundation and we encourage the use of the modified criteria over their original forms.

2013
Shaar, R, Tauxe L.  2013.  Thellier GUI: An integrated tool for analyzing paleointensity data from Thellier-type experiments. Geochemistry Geophysics Geosystems. 14:677-692.   10.1002/ggge.20062   AbstractWebsite

Thellier-type experiments are a method used to estimate the intensity of the ancient geomagnetic field from samples carrying thermoremanent magnetization. The analysis of Thellier-type experimental data is conventionally done by manually interpreting data from each specimen individually. The main limitations of this approach are: (1) manual interpretation is highly subjective and can be biased by misleading concepts, (2) the procedure is time consuming, and (3) unless the measurement data are published, the final results cannot be reproduced by readers. These issues compound when trying to combine together paleointensity data from a collection of studies. Here, we address these problems by introducing the Thellier GUI: a comprehensive tool for interpreting Thellier-type experimental data. The tool presents a graphical user interface, which allows manual interpretation of the data, but also includes two new interpretation tools: (1) Thellier Auto Interpreter: an automatic interpretation procedure based on a given set of experimental requirements, and 2) Consistency Test: a self-test for the consistency of the results assuming groups of samples that should have the same paleointensity values. We apply the new tools to data from two case studies. These demonstrate that interpretation of non-ideal Arai plots is nonunique and different selection criteria can lead to significantly different conclusions. Hence, we recommend adopting the automatic interpretation approach, as it allows a more objective interpretation, which can be easily repeated or revised by others. When the analysis is combined with a Consistency Test, the credibility of the interpretations is enhanced. We also make the case that published paleointensity studies should include the measurement data (as supplementary files or as a contributions to the MagIC database) so that results based on a particular data set can be reproduced and assessed by others.