Using XRD to Characterize Sediment Sorting in a Mars Analog Glacio-Fluvio-Eolian Basaltic Sedimentary System in Iceland
Bibliographic record
Abstract
The martian surface has a primarily basaltic composition and is dominated by sedimentary deposits. Ancient layered sedimentary rocks have been identified across the planet from orbit, have been studied in situ by the Mars Exploration Rovers and the Mars Science Laboratory rover, and will be studied by the Mars 2020 rover. These ancient sedimentary rocks were deposited in fluvial, lacustrine, and eolian environments during a warmer and wetter era on Mars. It is important to study the composition of sediments in Mars analog environments to characterize how minerals in basaltic sedimentary systems are sorted and/or aqueously altered. This information can help us better interpret sedimentary processes from similar deposits on Mars and derive information about the igneous source rocks. Sediment sorting has been studied extensively on Earth, but not typically in basaltic environments. Previous work has addressed sorting of basaltic sediments through experimental techniques and in modern eolian basaltic systems and aqueous alteration in subglacial and proglacial environments. We add to this body of research by studying sediment sorting and aqueous alteration in a glacio-fluvio-eolian basaltic system in southwest Iceland.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.000 | 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".