@article{proctor_2014, title={Comment on: "Utilizing Artificial Neural Networks in MATLAB to Achieve Parts-Per-Billion Mass Measurement Accuracy with a Fourier Transform Ion Cyclotron Resonance Mass Spectrometer" by D. Keith Williams Jr., Alexander L. Kovach, David C. Muddiman, and Kenneth W. Hanck. J-Am. Soc. Mass Spectrom. 20, 1303-1310 (2009)}, volume={25}, ISSN={["1879-1123"]}, DOI={10.1007/s13361-013-0805-8}, abstractNote={ADVERTISEMENT RETURN TO ISSUEPREVResearch ArticleNEXTComment on: “Utilizing Artificial Neural Networks in MATLAB to Achieve Parts-Per-Billion Mass Measurement Accuracy with a Fourier Transform Ion Cyclotron Resonance Mass Spectrometer” by D. Keith Williams Jr., Alexander L. Kovach, David C. Muddiman, and Kenneth W. Hanck. J. Am. Soc. Mass Spectrom. 20, 1303–1310 (2009)Charles ProctorCharles ProctorNorth Carolina State University, Raleigh, NC, USAMore by Charles ProctorCite this: J. Am. Soc. Mass Spectrom. 2014, 25, 4, 696Publication Date (Web):January 10, 2014Publication History Published online10 January 2014Published inissue 1 April 2014https://doi.org/10.1007/s13361-013-0805-8Copyright © 2014 © American Society for Mass Spectrometry 2014RIGHTS & PERMISSIONSArticle Views9Altmetric-Citations-LEARN ABOUT THESE METRICSArticle Views are the COUNTER-compliant sum of full text article downloads since November 2008 (both PDF and HTML) across all institutions and individuals. These metrics are regularly updated to reflect usage leading up to the last few days.Citations are the number of other articles citing this article, calculated by Crossref and updated daily. Find more information about Crossref citation counts.The Altmetric Attention Score is a quantitative measure of the attention that a research article has received online. Clicking on the donut icon will load a page at altmetric.com with additional details about the score and the social media presence for the given article. Find more information on the Altmetric Attention Score and how the score is calculated. Share Add toView InAdd Full Text with ReferenceAdd Description ExportRISCitationCitation and abstractCitation and referencesMore Options Share onFacebookTwitterWechatLinked InReddit Read OnlinePDF (61 KB) Get e-Alerts}, number={4}, journal={JOURNAL OF THE AMERICAN SOCIETY FOR MASS SPECTROMETRY}, author={Proctor, Charles}, year={2014}, month={Apr}, pages={696–696} }
 @article{proctor_2014, title={Comment to the Reply on: "Utilizing artificial neural networks in MATLAB to achieve parts-per-billion mass measurement accuracy with a Fourier transform ion cyclotron resonance mass spectrometer" by D. Keith Williams Jr., Alexander L. Kovach, David C. Mud}, volume={25}, number={4}, journal={Journal of the American Society for Mass Spectrometry}, author={Proctor, C.}, year={2014}, pages={698–698} }
 @article{proctor_2009, title={A Simple Definition of Detection Limit (vol 13, pg 99, 2008)}, volume={14}, ISSN={["1085-7117"]}, DOI={10.1198/jabes.2009.0008}, number={1}, journal={JOURNAL OF AGRICULTURAL BIOLOGICAL AND ENVIRONMENTAL STATISTICS}, author={Proctor, Charles H.}, year={2009}, month={Mar}, pages={133–133} }
 @article{proctor_2008, title={A simple definition of detection limit}, volume={13}, ISSN={["1537-2693"]}, DOI={10.1198/108571108X273476}, abstractNote={The detection limit of an analytical method tells how low a concentration can be said to be measured. Users, laboratories, and equipment manufacturers prefer low ones. Industries under environmental regulation insist on honest ones. However, the detection limits of environmental regulations generally refer to relatively complex detection experiments (assays) or surveys that differ from the simple measurement operation that gave rise to the detection limit concept in analytical chemistry. The first contribution of this article is to clarify the limited scope of the simple definition and then define the population quantity that is being estimated. Such specificity allows alternative estimates to be evaluated more on statistical grounds of bias and variance rather than on whether they push the resulting value up or down. The fundamental statistical problem is to fit a variance function so that the derived relative standard deviation (RSD) function of concentration is smooth and monotone decreasing and thus can be inverted. The solution is to accept the best-fitting analytical version of the RSD function (log-log and hybrid models are described), fit it, invert it to get the point estimate, and provide a jackknife standard error.}, number={1}, journal={JOURNAL OF AGRICULTURAL BIOLOGICAL AND ENVIRONMENTAL STATISTICS}, author={Proctor, Charles H.}, year={2008}, month={Mar}, pages={99–120} }
 @inbook{robarge_boos_proctor_2004, title={Determination of trace metal content of fertilizer source materials produced in north America}, volume={872}, DOI={10.1021/bk-2004-0872.ch006}, abstractNote={There is increasing concern over the trace metal content of fertilizers and their subsequent application to agricultural and urban lands. It is feared that continued addition of trace metals to soils via fertilizers poses potential risks to farm families and to consumers of farm products. In order to assess this potential risk, it is necessary to know the trace metal content of fertilizer source materials. This study was undertaken to generate a statistically valid sampling of fertilizer source material produced in North America, and to determine the trace metal content (As, Cd, Cr, Cu, Mo, Ni, Pb, Se, V, U and Zn) of the resulting composite samples generated by the sampling protocol using modern analytical instrumentation and accepted good laboratory practices. The results support the general hypothesis that phosphate bearing source materials do contain varying levels of trace metals. The results also demonstrate that non-phosphate bearing N-P-K source materials do not contain significant amounts of trace metals and should not be considered significant sources of metals when added to agricultural or urban soils. Agreement of analyses from an interlaboratory comparison demonstrate the suitability of the analytical protocols used in this study.}, number={2004}, booktitle={Environmental impact of fertilizer on soil and water}, publisher={Washington, D.C.: Transportation Research Board}, author={Robarge, W. P. and Boos, D. and Proctor, C.}, year={2004}, pages={75–89} }