Eagle-Tripati LaboratoriesGuide for clumped isotope data quality assessment, including measurement flagging December 2022 J. Lucarelli and A. Tripati • Definitions:○ Data quality assessment: the process of assessing if data are reproducible, including identifying if there were statistical outliers that may arise due to incomplete sample digestion, voltage fluctuations, exchange with water, carousel not advancing properly, or other processes relating to sample reaction, purification, and measurement, etc., resulting in an erroneous measurement or non-representative value ○ Flagging: identifying a statistical outlier that you hypothesize is due to an erroneous measurement or is not representative of the sample, that you think should not be included in calculations.■ You need ≥3 replicates to begin flagging. ○ Outlier: an observation that statistically lies an abnormal distance from other values in a random sample from a population. ○ Exclusion: removal of an analysis from the population.■ Before excluding a replicate, talk to Aradhna/Rob and Ben about why it's being excluded -there may be a solution to the issue. ■ You must include detailed notes on the justification in both the run log and in Easotope, after discussion with Aradhna/Rob and Ben ○ Standard deviation: a measure of the amount of variation or dispersion of a set of values.A low standard deviation indicates that the values tend to be close to the mean (also called the expected value) of the set, while a high standard deviation indicates that the values are spread out over a wider range.

No abstract