Formation and evolution of buried snowpack deposits in Pearse Valley, Antarctica, and implications for Mars
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Buried snowpack deposits are found within the McMurdo Dry Valleys of Antarctica, which offers the opportunity to study these layered structures of sand and ice within a polar desert environment. Four discrete buried snowpacks are studied within Pearse Valley, Antarctica, through in situ observations, sample analyses, O-H isotope measurements and numerical modelling of snowpack stability and evolution. The buried snowpack deposits evolve throughout the year and undergo deposition, melt, refreeze, and sublimation. We demonstrate how the deposition and subsequent burial of snow can preserve the snowpacks in the Dry Valleys. The modelled lifetimes of the buried snowpacks are dependent upon subsurface stratigraphy but are typically less than one year if the lag thickness is less than c. 7 cm and snow thickness is less than c. 10 cm, indicating that some of the Antarctic buried snowpacks form annually. Buried snowpacks in the Antarctic polar desert may serve as analogues for similar deposits on Mars and may be applicable to observations of the north polar erg, buried ice at the Mars Phoenix landing site, and observations of buried ice throughout the martian Arctic. Numerical modelling suggests that seasonal snows and subsequent burial are not required to preserve the snow and ice on Mars.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.002 |
| 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 it