3D imaging of Mars’ shallow subsurface with orbital radar data
Bibliographic record
Abstract
Since November 2006, the Shallow Radar (SHARAD) aboard the U.S. National Aeronautics and Space Administration’s (NASA’s) Mars Reconnaissance Orbiter (MRO) has been conducting subsurface sounding operations from orbit around Mars. This extended campaign has provided tens of thousands of radar profiles of Mars shallow subsurface, with coverage density in some regions having become sufficient for performing three-dimensional (3D) imaging. Adapting methods and tools used to produce, analyze, and interpret terrestrial seismograms, we have produced and studied fully imaged 3D radargrams in Mars’ polar and mid-latitudes regions. In this report, we provide some background on the SHARAD instrument, summarize the methods and tools used in creating 3D radargrams from SHARAD data, and present example views from the latest 3D radargram in the north polar region known as Planum Boreum (PB).
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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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".