High‐Resolution Thermophysical Analysis of the OSIRIS‐REx Sample Site and Three Other Regions of Interest on Bennu
Bibliographic record
Abstract
Abstract The OSIRIS‐REx (Origins, Spectral Interpretation, Resource Identification, and Security–Regolith Explorer) spacecraft sampled asteroid (101955) Bennu on 20 October 2020 and will return the collected regolith to Earth in 2023. Before sample collection, spectral observations of four regions of interest on Bennu's surface were acquired at high spatial resolution (2–9 m per spectrometer spot) to identify the most suitable site for sampling and provide contextual information for the returned sample. In this study, we investigate thermal‐infrared (6–50 μm) observations of these four regions, including the site that OSIRIS‐REx ultimately sampled, using the Advanced Thermophysical Model with input digital terrain models derived from laser altimetry. From model‐to‐measurement comparisons, we find that the observed brightness temperatures depend strongly on small‐scale topography, local variations in thermal inertia, and the observation phase angle. Thermal inertia mapping reveals spatial variations that distinguish the different boulder types found on Bennu. A boulder bearing carbonate veins has higher thermal inertia than average, suggesting that cementation processes reduced its porosity. The thermal inertia of the site sampled is 190 ± 30 J m−2 K−1 s−1/2, which is consistent with observations of a fine‐grained regolith mixed with porous rocks. Thermophysical modeling of the site sampled predicts that the maximum temperatures experienced by the collected sample while on Bennu were 357 ± 3 and 261 ± 3 K for the surface and 50 cm depth, respectively. We predict that OSIRIS‐REx will return a sample with thermophysical properties unique from those of meteorites.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".