Hydrothermal processes at Gusev Crater: An evaluation of Paso Robles class soils
Bibliographic record
Abstract
The Mars Exploration Rover Spirit analyzed multiple occurrences of sulfur‐rich, light‐toned soils along its traverse within Gusev Crater. These hydrated deposits are not readily apparent in images of undisturbed soil but are present at shallow depths and were exposed by the actions of the rover wheels. Referred to as “Paso Robles” class soils, they are dominated by ferric iron sulfates, silica, and Mg‐sulfates. Ca‐sulfates, Ca‐phosphates, and other minor phases are also indicated in certain specific samples. The chemical compositions are highly variable over both centimeter‐scale distances and between the widely separated exposures, but they clearly reflect the elemental signatures of nearby rocks. The quantity of typical basaltic soil mixed into the light‐toned materials prior to excavation by the rover wheels is minimal, suggesting negligible reworking of the deposits after their initial formation. The mineralogy, geochemistry, variability, association with local compositions, and geologic setting of the deposits suggest that Paso Robles class soils likely formed as hydrothermal and fumarolic condensates derived from magma degassing and/or oxidative alteration of crustal iron sulfide deposits. Their occurrence as unconsolidated, near‐surface soils permits, though does not require, an age that is significantly younger than that of the surrounding rocks.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".