Rocks with Extremely Low Thermal Inertia at the OSIRIS-REx Sample Site on Asteroid Bennu
Bibliographic record
Abstract
Abstract The Origins, Spectral Interpretation, Resource Identification, and Security–Regolith Explorer (OSIRIS-REx) mission recently returned a sample of rocks and dust collected from asteroid Bennu. We analyzed the highest-resolution thermal data obtained by the OSIRIS-REx Thermal Emission Spectrometer (OTES) to gain insight into the thermal and physical properties of the sampling site, including rocks that may have been sampled, and the immediately surrounding Hokioi Crater. After correcting the pointing of the OTES data sets, we find that OTES fortuitously observed two dark rocks moments before they were contacted by the spacecraft. We derived thermal inertias of 100–150 (±50) J m−2 K−1 s−1/2 for these two rocks—exceptionally low even compared with other previously analyzed dark rocks on Bennu (180–250 J m−2 K−1 s−1/2). Our simulations indicate that monolayer coatings of sand- to pebble-sized particles, as observed on one of these rocks, could significantly reduce the apparent thermal inertia and largely mask the properties of the substrate. However, the other low-thermal-inertia rock that was contacted is not obviously covered in particles. Moreover, this rock appears to have been partially crushed, and thus potentially sampled, by the spacecraft. We conclude that this rock may be highly fractured and that it should be sought in the returned sample to better understand its origin in Bennu’s parent body and the relationship between its thermal and physical properties.
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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 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".