Effective Correction of Mass Bias for Rhenium Measurements by MC‐ICP‐MS
Bibliographic record
Abstract
The geochemistry of Re‐Os and the recent use of Re as a non‐traditional stable isotope both need accurate and precise quantification of 187Re/185Re ratios. This paper reports rhenium isotopic data obtained from the analysis of a standard solution and geological samples by MC‐ICP‐MS. We show that measured isotopic ratios are modified by matrix effects that cannot be accounted for by the standard solution bracketing technique. The bias resulting from measurements on a spiked (185Re‐enriched) sample is shown to alter the apparent Re concentration by several percent. When spiking samples and calibrators with tungsten, simultaneous measurement of tungsten and rhenium isotopes compensates for the matrix‐induced modification of mass bias. Rhenium and tungsten are shown to have different fractionation factors. This may be due to the fact that the two elements fractionate in a different but systematic way, or that the reference isotopic ratios used for elemental Re and W are incoherent with one another. The consistency of fractionation through time can be used to obtain an empirical relationship between W and Re measured ratios from a standard solution to obtain a sample's fractionation‐corrected 187Re/185Re spiked ratio on samples containing pg g−1 levels of Re, even if some matrix capable of affecting mass bias remains in the final solution.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".