The oxygen isotope compositions of olivine in main group (<scp>MG</scp>) pallasites: New measurements by adopting an improved laser fluorination approach
Bibliographic record
Abstract
Abstract Oxygen isotope measurements of olivine in main group ( MG ) pallasites by traditional laser fluorination method are associated with some uncertainties including terrestrial weathering, incomplete olivine reaction, and sample state. We improved our laser fluorination approach by pretreating olivine grains with acid to remove terrestrial weathering products and by modifying the sample holder for an efficient and complete laser reaction. Our experiments on Brahin olivine demonstrate that acid‐washing successfully removes the terrestrial weathering with <0.1‰ variation in δ 18 O value and, at the same time, improving the ∆ 17 O value significantly. We also achieved a complete olivine fluorination by employing a custom‐designed sample holder with “V”‐shaped profile having rounded bottom because incomplete/partial reaction of olivine gives comparatively lighter δ 18 O values. Using these new techniques, we present precise triple oxygen isotope data ( N = 72) of 25 olivine samples separated from main group pallasites. The data are, on average, ~0.5‰ heavier in δ 18 O relative to the values published in the literature for the same samples. Critically, the ∆ 17 O values of MG pallasites and to some extent their Fo‐contents suggest that there are at least two populations of olivine. Based on our improved data set, we propose that MG pallasites potentially have high‐∆ 17 O‐ and low‐∆ 17 O‐bearing subgroups that are statistically distinct. The subgroups present average ∆ 17 O values of −0.166 ± 0.003 (2 SE ; N = 16) and −0.220 ± 0.003 (2 SE ; N = 9), respectively. Furthermore, the high‐∆ 17 O‐bearing subgroup samples trend toward lower Fo‐contents compared to the other subgroup. Taken together, our data provide evidence that argues against a single parent body origin for MG pallasites.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".