Gravity modeling of lunar lava tubes: Insights from Ape Cave as a terrestrial analogue
Bibliographic record
Abstract
The files presented here serve as a repository for the datasets generated during the research Gravity Modeling of Lunar Lava Tubes: Insights from Ape Cave as a Terrestrial Analogue. The material includes the following: Gravity_Field_Corrected.csv: contains the corrected gravity data collected from four transects at Ape Cave (WA, USA) in June 2023. Gravity_Forward_Ape_Cave.csv: synthetic results obtained from the gravity forward modeling of Ape Cave, using a density contrast of 2746 kg/m³ and a high-resolution 3D model of the cave. Gravity_Lunar_North.csv and Gravity_Lunar_South.csv: synthetic results obtained from the gravity forward modeling of a lunar lava tube with Ape Cave dimentions and a density contrast of 3270 kg/m³, a minimum depth of 26 m and two layers of regolith with a combined thickness of 5 m. The model was split into North and South sections due to model size constraints. Gravity_Lunar_Scaled_North.csv and Gravity_Lunar_Scaled_South.csv: synthetic results obtained from the gravity forward modeling of a lunar lava tube five times larger than Ape Cave, a density contrast of 3270 kg/m³, a minimum depth of 26 m and two layers of regolith with a combined thickness of 5 m. The model was split into North and South sections due to model size constraints.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".