Observations of Large Mass-Independent Fractionation Occurring in MC-ICPMS: Implications for Determination of Accurate Isotope Amount Ratios
Bibliographic record
Abstract
Multicollector inductively coupled plasma mass spectrometry (MC-ICPMS) suffers large bias in isotope amount ratio determinations which has to be properly accounted for. The choice of the proper discrimination model is crucial. Over the last few decades, the exponential mass-bias correction model (Russell's law) has become a standard curriculum in isotope amount ratio measurements. In nature, however, isotopic fractionation that deviates significantly from the exponential model has been known for a long time. Recently, such fractionation was also observed in MC-ICPMS. This phenomenon is termed mass-independent fractionation. In this study, significant departure from the mass-dependent fractionation model is reported for germanium and lead with the most dramatic occurring for germanium-73 and lead-204 isotopes wherein, on average, close to a half percent bias was evidenced from the Russell's law.
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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 | 0.006 |
| 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 | 0.001 | 0.001 |
| 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".