Application of Laser Ablation ICP‐MS to U‐Th‐Pb Dating of Monazite
Bibliographic record
Abstract
Recent advances in laser ablation ICP‐MS techniques allow accurate U‐Th‐Pb age dating of monazites that are as young as several tens of million years to a precision better than 2%. Accuracy of the age determinations has been improved by true real‐time mass bias correction via nebulisation of a solution containing enriched 233U and natural Tl isotopes. The Tl‐U tracer solution eliminates possible effects of variable sample matrices on the precision and accuracy of measured isotopic ratios. Mass bias corrections based on measured 205Tl/233U ratios in the tracer solution allow direct measurement of 235U in monazite. Combined with high‐sensitivity laser ablation ICP‐MS measurements, direct measurement of 235U particularly improves the precision of U‐Pb dating of young monazites. Correction for laser‐induced Pb/U and Pb/Th elemental fractionation is based on a mathematical treatment of time resolved count‐rate data that is independent of laser ablation characteristics, does not require external standardisation and allows variable laser pit size or raster patterns for each measurement. The new procedures make the LA ICP‐MS technique more flexible for in situ U‐Th‐Pb analysis.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".