Resolving oxygen isotopic disturbance in zircon: A case study from the low δ <sup>18</sup> O Scourie dikes, NW Scotland
Bibliographic record
Abstract
In this paper, we describe an in situ non-destructive technique to identify areas within zircon crystals that have experienced fluid exchange. We show that Raman spectroscopy combined with electron microprobe trace-element analysis can be used to pinpoint areas in altered, complexly zoned, and metamict zircon that record the original magmatic compositions. These techniques are developed on a suite of Paleoproterozoic zircon crystals from the Scourie dike swarm in the Archean gneiss terrane of NW Scotland that are known to be anomalously low in δ 18 O. We show that zircons from the Scourie dikes record extremely low-δ 18 O isotopic compositions down to approximately -3‰, which reflect their magmatic values. Zircon populations from the dikes have a range in δ 18 O from low values (<0‰) up to ~5‰ with no obvious relationship between oxygen isotopic composition and cathodoluminescence. Raman spectra from the zircons show evidence for fluid interaction in some areas of the grains because of partial recrystallization and atypical radiation damage properties. Electron microprobe analysis in the same areas documents high (>1000 ppm) U concentrations and high (>1000 ppm) abundances of non-formula Ca. When the combined Raman and electron microprobe data are used to filter the oxygen isotopic data, the fluid altered areas of the grains show consistently higher δ 18 O values than the areas without evidence for fluid alteration. The low-δ 18 O values therefore reflect the original magmatic composition of the grains and indicate that the Scourie dike magmas were low in 18 O. We suggest that these non-destructive techniques should be used prior to SIMS analysis of complex zircons to target the least disturbed areas of the grains.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".