The Need for Fission Track Data Transparency

Abstract. We report a new image-based inter-analyst study to investigate fission-track grain selection and analysis by 13 participants from an image data set that included grains of variable quality. Results suggest that participants with less experience show a higher rate of selecting unsuitable grains, while participants from the same laboratories generally provide similar results. Less analysis experience may result in the rejection of suitable grains, or inclusion of unsuitable ones. While inappropriate omission and inclusion can both bias results, the latter is more pernicious due to the standard practice of achieving a predecided number of analyses; particularly in difficult samples, there is a danger of “squeezing the rock” by weakening selection criteria. Juxtaposing selected regions of interest (ROIs) on the same grains indicates that zoned grains and grains with inclusions and defects yield varying track density estimates, indicating that ROI placement can be an influential factor. We propose developing image data repositories for global data transparency, a global guidance for fission-track analysis, digital teaching modules, and open science. We also point out the need for new approaches for zeta calibration that include consideration of grain quality, methods of uranium determination, and etching protocols.