Metrological Triangle for Measurements of Isotope Amount Ratios of Silver, Indium, and Antimony Using Multicollector-Inductively Coupled Plasma Mass Spectrometry: The 21st Century Harvard Method
Bibliographic record
Abstract
The calibration of measurements of the isotope amount ratio using a log-linear regression method with multicollector-inductively coupled plasma mass spectrometry (MC-ICPMS) is the latest development in isotope amount ratio metrology. This calibration method, however, is often met with criticism. In this work, we evaluate the robustness of this calibration strategy wherein measurements of antimony and indium isotope amount ratios are calibrated against the isotope amount ratio of silver, despite the significant difference in their atomic mass. In addition, a metrological triangle comprising Ag-Sb-In measurement results is constructed from three pairs of interelemental isotope amount ratio calibrations: N((121)Sb)/N((123)Sb) from the N((107)Ag)/N((109)Ag) of NIST SRM 978a measurement standard, N((113)In)/N((115)In) from the N((121)Sb)/N((123)Sb), and then calibration of N((107)Ag)/N((109)Ag) from the obtained N((113)In)/N((115)In) measured ratio values to verify consistency with the known N((107)Ag)/N((109)Ag). This calibration method revives one of the salient features of the classical "Harvard method", a network of relationships among the isotopic compositions of various elements. The atomic weights of antimony and indium, reported here for the first time using MC-ICPMS, 121.7590(22)(k=2) and 114.818 27(35)(k=2), are in good agreement with their current standard atomic weights. In addition, this study provides the first calibrated mass spectrometric isotope amount ratio measurements for indium.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.002 |
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 source (direct Gemma or distilled Codex), 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".