Petrographic controls on baddeleyite occurrence in a suite of eight basaltic shergottites
Bibliographic record
Abstract
Abstract Baddeleyite (ZrO2) is a common late‐stage accessory mineral in basaltic shergottites and is a robust geochronometer for obtaining igneous crystallization ages via high‐precision in situ SIMS U‐Pb analysis. Amenability to SIMS U‐Pb dating depends in large part on the size and abundance of baddeleyite grains, which are generally surveyed using microbeam methods. We examine the petrography, mineralogy, geochemistry, and baddeleyite distribution in eight basaltic shergottites to identify factors that may be used to predict baddeleyite distribution in unknown samples of Mars. Results suggest that fractional crystallization controls baddeleyite occurrence in shergottites to the first order; samples with pyroxene major element compositions extending beyond the 1‐bar stability boundary generally have higher baddeleyite abundance compared with samples with pyroxene compositions terminating at or before the stability boundary. In samples which display two pyroxene composition trends (high‐Ca and low‐Ca), the largest baddeleyite grains tend to be associated with Fe‐Ti oxides; in samples where pyroxene composition forms a continuous trend extending beyond the 1‐bar stability boundary, the largest baddeleyite grains are typically associated with polymineralic late‐stage pockets. Bulk HFSE content and fO2 do not appear to directly influence baddeleyite distribution. Based on our findings, we propose that pyroxene composition is a useful proxy for assessing baddeleyite abundance and distribution in shergottites and may aid in determining a sample’s feasibility for U‐Pb geochronology prior to conducting detailed surveys for baddeleyite characterization.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 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) | 0.001 | 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".