Assessing global trends in Mars magma compositions using ground truth
Bibliographic record
Abstract
Abstract Global magmatic trends inferred from gamma‐ray, visible/near‐infrared, and thermal infrared spectrometers on Mars‐orbiting spacecraft have been used to constrain planetary petrogenetic processes and global thermal evolution models. Inferred magmatic trends include temporal variations in the relative proportions of low‐Ca and high‐Ca pyroxenes, and in the abundances of potassium (and total alkalis), silica, FeO* (total iron expressed as FeO), and thorium. These patterns are evaluated for consistency with the compositions of surface igneous rocks of different ages analyzed by Mars rovers and of martian meteorites. Trends of decreasing low‐Ca pyroxene/total pyroxene ratios and of decreasing potassium (and total alkalis), with time are generally supported by surface rock analyses. However, significant differences in the GRS‐measured silica in Amazonian volcanoes and in martian meteorites of equivalent age result from contamination by silica‐rich dust and are problematic for a silica trend. Comparison of FeO* in Noachian and Amazonian surface data shows no decrease. An inferred temporal trend in thorium is in conflict with the complex enrichment and depletion patterns of incompatible trace elements in martian meteorites of various ages. A dearth of analyses of Hesperian‐age surface rocks precludes a firm evaluation of inferred Noachian‐Hesperian trends and Hesperian‐Amazonian trends, but abundant Noachian rocks and a few Hesperian rocks at rover sites, and Amazonian martian meteorites, collectively representing at least 16 surface locations, afford useful comparisons with orbital remote‐sensing data.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".