Dating Micrometre‐Thin Rims Using a <scp>LA</scp>‐<scp>ICP</scp>‐<scp>MS</scp> Depth Profiling Technique on Zircon from an Archaean Metasediment: Comparison with the <scp>SIMS</scp> Depth Profiling Method
Bibliographic record
Abstract
Laser ablation‐inductively coupled plasma‐mass spectrometry ( LA ‐ ICP ‐ MS ) was examined as a tool for measuring isotopic variation as a function of ablation depth in unpolished zircon from an Archaean metasediment specimen. This technique was able to identify micrometre‐thin (> 3 μm) isotopically distinct mineral domains characterised by ca . 100 Myr younger 207 Pb/ 206 Pb ages associated with 2 s age uncertainties as low ~ 0.2%, as well as elevated U content relative to grain interiors (up to an order of magnitude). Our calculated drilling rate suggests that each laser pulse excavated depths of ~ 0.06 μm. Ages resolved through the LA ‐ ICP ‐ MS methods overlap the 2 s uncertainties of 207 Pb/ 206 Pb ages measured using SIMS depth profiling on the same zircon population. The rims were further evinced by the detection of relative enrichment (> 3 orders of magnitude) in REE in the outermost micrometres of the same zircon, measured using a different and independent LA ‐ ICP ‐ MS depth profiling technique. We propose a LA ‐ ICP ‐ MS U–Pb technique capable of quickly identifying and quantifying rims, which are indication of late, yet geologically significant, fluid events that are otherwise undefined.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".