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Record W4412120344 · doi:10.5194/epsc-dps2025-717

Beyond Bulk Chemistry: Enhancing the Science Return of Landed In Situ X-ray Spectrometers

2025· preprint· en· W4412120344 on OpenAlexaff
S. J. VanBommel, J. A. Berger, Abigail L. Knight, W. E. Dietrich, Daniel Lo, R. Gellert

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldPhysics and Astronomy
TopicX-ray Spectroscopy and Fluorescence Analysis
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsIn situSpectrometerX-rayEngineering physicsNanotechnologyMaterials sciencePhysicsOpticsMeteorology

Abstract

fetched live from OpenAlex

X-ray fluorescence (XRF) spectroscopy has long served as a cornerstone analytical technique in planetary surface exploration, enabling high-precision compositional analyses of planetary materials in situ. On Mars, two prominent XRF instruments — the Alpha Particle X-ray Spectrometer (APXS) aboard Curiosity and the Planetary Instrument for X-ray Lithochemistry (PIXL) aboard Perseverance — have demonstrated that the capabilities of landed XRF instruments extend beyond the quantification of bulk chemistry. Native Sulfur on MarsAPXS has performed ~1700 compositional analyses since Curiosity landed in Gale crater in 2012. While APXS traditionally derives bulk rock and soil compositions, systematic advancements have been made that enable the assessment of distinct features on the sub-cm scale, smaller than the APXS field of view (e.g., [1]). This advancement, combined with the capability to characterize light‑element (i.e., Z

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.017
Threshold uncertainty score0.056

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.008
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0050.011
Open science0.0020.004
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0170.010

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 head0.007
GPT teacher head0.255
Teacher spread0.248 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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

Citations1
Published2025
Admission routes1
Has abstractyes

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