Determination of natural isotopic variation in nickel using inductively coupled plasma mass spectrometry
Bibliographic record
Abstract
In this study, we measured natural isotopic variation of terrestrial nickel using multiple-collector inductively coupled plasma mass spectrometry. External precisions in 58Ni/62Ni, 60Ni/62Ni, 61Ni/62Ni, and 64Ni/62Ni ratios of 0.02%, 0.01%, 0.04%, and 0.09% (2 × standard deviation), respectively, were routinely obtainable for a Ni isotopic reference standard by correcting the mass discrimination effect with a 65Cu/63Cu ratio of 0.4456. Only a small isotopic variation of ±0.15‰ amu−1 was observed among seven commercially available reagent-grade nickel metals, while variation of ±0.20‰ amu−1 was observed for two nickel sulfide samples from Canada. The isotopic compositions of the two types of samples overlap. The overall variation of ±0.25‰ amu−1 corresponds to an uncertainty of 0.000 37 for the atomic weight of nickel; this uncertainty is twice the currently recommended value (56.6934 ± 0.0002) for the standard atomic weight of terrestrial nickel as proposed by IUPAC.
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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 | 0.000 | 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 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".