Detection of Inconsistencies in Isotope Ratios Certified in the Isotopic Primary Standards for Copper, Zinc and Nickel
Bibliographic record
Abstract
Calibrated isotope ratio measurements underpin numerous areas of scientific enquiry. Isotope measurement results rely on reference materials in order to correct instrumental isotopic fractionation, a bias induced by all mass spectrometers. The reference values assigned to these materials are typically obtained using gravimetric mixtures of separated isotopes but such experiments are costly and thus rarely cross‐examined. Here we advance the concept of linking measurements of various isotope systems to provide a cost‐effective way to assess the reliability of the values assigned to isotopic primary standards. Using MC‐ICP‐MS, we apply this workflow to examine the consistency of a couple of long‐standing isotopic primary standards of copper, nickel and zinc. Our measurement results of the reference materials that define the isotope ratios and consequently the atomic weights of zinc and nickel, A r (Zn, IRMM‐3702) = 65.3604 ± 0.0023 (95% confidence interval) and A r (Ni, NIST SRM 986) = 58.6979 ± 0.0010 (95% confidence interval), show zinc to be 15‐sigma lighter and nickel 16‐sigma heavier than their certified values. These discrepancies are suggestive of a wider reproducibility crisis surrounding isotopic standards and a further cross‐examination of isotope ratios associated with primary reference materials is likely to identify yet‐unrecognised biases for many other elements of the Periodic Table leading to improvements of the overall reliability of research conclusions that relies on them.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".