Quantitative in situ determination of hydration of bright high‐sulfate Martian soils
Bibliographic record
Abstract
The total water content of soils and rocks encountered by the Spirit rover has been determined by a new analysis method applied to the existing data from the Alpha Particle X‐Ray Spectrometer (APXS). This approach employs Monte Carlo simulation of the intensities of the photon scatter peaks in the APXS spectra, together with extraction of these intensities from the spectra. For any individual sample, the water detection limits (∼6 wt %) and error bars are high due to low counting statistics in the spectra, but combining the data from a well‐defined group of similar samples improves the error bars and lowers the limit. Thus typical basaltic surface soils are found to be essentially dry (<1 wt % water) and basaltic rocks are very close to dry (<3.5 wt % water). For four bright subsurface soils in Gusev Crater the water content lies in the range 6–18 wt %; these soils contain sulfur at unusually high levels (>12 wt %, 30 wt % SO3) relative to the soils common at other landing sites. Mass balance mixing calculations of available cations infer the presence of Fe‐, Mg‐, and Ca‐sulfates in these bright soils. Together with constraints from mineralogy, our results imply that highly hydrated ferric sulfates are the most important carrier of the bound water found in these four spots. In conjunction with the complementary available chemical and mineralogical information they reveal additional information about present bound water reservoirs on Mars, their mineralogy and their spatial and lateral distribution along the Spirit rover's traverse.
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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 | 0.000 | 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) | 0.001 | 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".