Resolving the Germanium Atomic Weight Disparity Using Multicollector ICPMS
Bibliographic record
Abstract
Two most recent mass spectrometric measurements of natural isotopic composition germanium gave discordant Ge atomic weight values of 72.6276(64)(k=2) and 72.6390(69)(k=2), respectively, a decade ago. Each measurement was performed with a different mass spectrometry platform, gas source isotope ratio mass spectrometry and thermal ionization mass spectrometry, respectively. Herein we report results obtained by multicollector inductively coupled plasma mass spectrometry yielding an atomic weight of germanium 72.6296(19)(k=2) which is in support of the upcoming 2009 Standard Atomic Weight adjustment by IUPAC. Germanium isotope ratios were calibrated using a regression mass bias correction model and NIST SRM 994 gallium isotopic reference material. In this model, no assumptions are made regarding the mass bias differences between gallium and germanium or between the isotopes of germanium. Isotope ratios of 0.5620(21), 0.7515(16), 0.2125(7), and 0.2121(12) were obtained for n((70)Ge)/n((74)Ge), n((72)Ge)/n((74)Ge), n((73)Ge)/n((74)Ge), and n((76)Ge)/n((74)Ge), respectively, with expanded uncertainties (k = 2) estimated in accordance with the ISO/BIPM Guide to the Expression of Uncertainty in Measurements.
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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 | 0.002 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".