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Record W3188099135 · doi:10.1111/maps.13726

Petrographic controls on baddeleyite occurrence in a suite of eight basaltic shergottites

2021· article· en· W3188099135 on OpenAlexafffund
Alex I. Sheen, C. D. K. Herd, Jarret Hamilton, E. L. Walton

Bibliographic record

VenueMeteoritics and Planetary Science · 2021
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicPaleontology and Stratigraphy of Fossils
Canadian institutionsMacEwan UniversityUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsBaddeleyitePyroxeneGeologyGeochemistryPetrographyMineralogyOlivineZircon

Abstract

fetched live from OpenAlex

Abstract Baddeleyite (ZrO 2 ) 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 f O 2 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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.028
Threshold uncertainty score0.561

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.012
GPT teacher head0.219
Teacher spread0.207 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations10
Published2021
Admission routes2
Has abstractyes

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