Evaluating measurements with high intrinsic error (interdisciplinary research)

With this message I would like to address people in research and development interested in collaborations evaluating a novel method for
variables technically hard to measure.
Recently I have specialized in the evaluation of measurements that, because of multiple factors contributing to the apparent error, provide only low precision results. Such intrinsic error used to contaminate massively the identification of changes for the objects measured.
To overcome this problem, I developed a method to identify, and gradually disqualify, low quality data. This procedure succeeded in minimizing dramatically the risk of detecting false positives without loosing true positives.
I am interested in identifying and testing additional (novel) applications for this type of evaluation. This method is particularly useful for trend-analysis and/or evaluating input generated from multiple parallel sensors.
If you have a potential application, I would appreciate the opportunity to discuss this with you in more detail. Please contact me at w snipped-for-privacy@yahoo.com .
Sincerely, Wolfgang Raffelsberger
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