Measurement of Pb isotope ratios by continuous leach–inductively coupled plasma–mass spectrometry: quantification of precision and accuracy
Bibliographic record
Abstract
Precision and accuracy have been quantified for the determination of lead isotope ratios using continuous leach–inductively coupled plasma–mass spectrometry (CL-ICP-MS) by optimizing acquisition parameters and minimizing the number of elements in the method. By analysing for only 204 Pb, 206 Pb, 207 Pb, 208 Pb, 200 Hg, and 202 Hg, counting times can be increased allowing improvements in isotope ratio precision over normal CL-ICP-MS determinations, which measure these elements as part of a much larger suite. At total Pb concentrations of 1 ppb in solution, results show that precisions of 6.7% to 8.3% and 7.8% to 21% can be achieved for 207 Pb/ 206 Pb and 207 Pb/ 204 Pb, respectively, over the 0% to 30% HNO 3 concentrations used in CL-ICP-MS. Accuracy, as measured against the certified values for NIST 981, ranges from 0.5% to 1.4% and 1.4% to 21% for 207 Pb/ 206 Pb and 207 Pb/ 204 Pb, respectively. The improvement in precision and accuracy afforded by this technique allows greater differentiation of isotopically distinct reservoirs of Pb within natural samples collected for exploration and environmental geochemistry.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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".