Measurement of SIMS Instrumental Mass Fractionation of Pb Isotopes During Zircon Dating
Bibliographic record
Abstract
An igneous zircon reference material (OG1) was characterised for U‐Pb isotopes by ID‐TIMS, and utilised to evaluate SIMS (SHRIMP) instrumental mass fractionation (IMF) of radiogenic Pb isotopes ( 207 Pb*/ 206 Pb*). The TIMS 207 Pb*/ 206 Pb* reference value for OG1 was 0.29907 ± 0.00011 (95% confidence limit), 3465.4 ± 0.6 Ma. The high 207 Pb* (∼ 30 μg g −1 ), negligible common Pb, and isotopic homogeneity permitted precise (± 1–2‰) 207 Pb*/ 206 Pb* measurements within the analytical sessions. External reproducibility of mean 207 Pb*/ 206 Pb* ratios between sessions was demonstrated for one instrument, yielding a mean IMF of +0.87 ± 0.49‰. The mean 207 Pb*/ 206 Pb* ratios between instruments were dispersed beyond uncertainties, with session IMF values from +3.6 ± 1.7‰ to −2.4 ± 1.3‰, and a grand mean IMF value (twenty‐six sessions) of +0.70 ± 0.52‰, indicating a tendency towards elevated 207 Pb*/ 206 Pb*. The specific causes of variability in IMF are unclear, but generally reflect subtle differences in analytical conditions. The common practice in SIMS of assuming that IMF for Pb + is insignificant could result in systematic age biases and underestimated uncertainties, of critical importance for precise correlation of Precambrian events. Nevertheless, a zircon RM such as OG1 can be readily incorporated into routine dating to improve 207 Pb*/ 206 Pb* accuracy and external reproducibility.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".