Impact Resurfacing of the Artemis Exploration Zone: Sample Locations for Primordial Crust and South Pole‐Aitken (SPA) Ejecta
Bibliographic record
Abstract
Abstract Regolith samples from the lunar south pole are expected to contain material from the ancient lunar crust and potentially the uppermost mantle, excavated by the South Pole‐Aitken (SPA) impact. In this study, we aim to understand the impact resurfacing processes following the SPA impact and the subsequent redistribution of primordial crust and SPA‐derived mantle material within the initial Artemis exploration zone (AEZ). Our goal is to identify optimal sampling locations for these materials. To achieve this, we reconstruct the south pole stratigraphy by modeling the cumulative thickness of post‐SPA crater materials and estimating the present SPA ejecta thickness. By calculating crater excavation depths, we then infer which craters were excavated from what stratigraphic layer. We estimate a cumulative post‐SPA ejecta layer thickness of ∼190 m to ∼1.8 km across different locations. We infer that all craters >10 km in diameter within the AEZ have likely been excavated below the post‐SPA regolith layer. Based on surficial presence of anorthositic and mafic material, we postulate an SPA ejecta thickness in the AEZ of several hundred meters up to ∼10 km. The extent to which primordial crust and SPA‐derived mantle material have been excavated depends on the wide range of possible SPA ejecta thicknesses. Their surficial presence and sampling potential are influenced by the age of the excavating crater. By integrating the stratigraphic model with mineral maps, we identify promising sampling targets, including regolith with potentially concentrated SPA material in the ejecta blanket of Kocher and primordial crust in the ejecta blanket of Shackleton crater.
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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 | 0.001 |
| 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 | 0.000 | 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".