<b>Mass bias corrections for U‐Pb isotopic analysis by secondary ion mass spectrometry: Implications for U‐Pb dating of uraninite</b>
Bibliographic record
Abstract
RATIONALE: Uranium (U)-lead (Pb) geochronology of uraninite is critical to the study of the genesis of U deposits throughout the world. Previous attempts at developing a technique to date uraninite using secondary ion mass spectrometry (SIMS) have, however, had limited success. Improper correction of mass bias results in incorrect reported U-Pb ratios. When these results are plotted on Concordia diagrams they produce erroneous ages, complicating the study of U deposits. METHODS: Uranium and Pb isotope ratios were measured in three uraninite reference materials (RMs) with varying Pb content and three samples with unknown U-Pb isotope compositions using a CAMECA 7f SIMS instrument. Measurements were made using a primary beam of O(-) accelerated at 12.5 kV. A mass resolving power of 1300 and a 50-V offset were used to minimize interferences. RESULTS: The study demonstrates that the mass bias for U-Pb isotope ratio measurements in uraninite by SIMS varies as a function of Pb content. A three-point calibration curve was developed using uraninite RMs with low-, intermediate- and high-Pb contents. Corrected ratios for both concordant and discordant uraninite were plotted on a Concordia diagram to demonstrate the effect that different correction techniques have on the resulting age. CONCLUSIONS: Accurate determination of U-Pb ratios in uraninite using a SIMS instrument requires a suite of RMs with varying Pb content and the construction of a calibration curve, or a uraninite RM with a Pb content similar to that of the unknowns. Failure to standardize correctly will result in erroneous ages being calculated using Concordia diagrams. Copyright © 2016 John Wiley & Sons, Ltd.
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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 | 0.007 |
| 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 | 0.001 |
| 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".