OSIRIS-REx spectral analysis of (101955) Bennu by multivariate statistics
Bibliographic record
Abstract
Contact.The NASA New Frontiers asteroid sample return mission Origins, Spectral Interpretation, Resource Identification, and Security–Regolith Explorer (OSIRIS-REx) has provided a large amount of data on the asteroid (101955) Bennu, including high-quality spectra obtained by the OSIRIS-REx Visible and InfraRed Spectrometer (OVIRS). Aims.To better constrain the surface properties and compositional variations of Bennu, we studied the visible and near-infrared spectral behavior across the asteroid surface by means of a statistical analysis aiming to distinguish spectrally distinct groups, if present. Methods.We applied theG-mode multivariate statistical analysis to the near-infrared OVIRS spectra to obtain an automatic statistical clustering at different confidence levels. Results.The statistical analysis highlights spectral variations on the surface of Bennu. Five distinct spectral groups are identified at a 2σconfidence level. At a higher confidence level of 3σ, no grouping is observed. Conclusions.The results at a 2σconfidence level distinguish a dominant spectral behavior group (group 1, background) and four small groups showing spectral slope variations, associated with areas with different surface properties. The background group contains most of the analyzed data, which implies a globally homogeneous surface at the spectral and spatial resolution of the data. The small groups with redder spectra are concentrated around the equatorial ridge and are associated with morphological surface features such as specific craters and boulders. No significant variation is detected in the band area or depth of the 2.74μm band, which is associated with hydrated phyllosilicate content. The spectral slope variations are interpreted as a consequence of different regolith particle sizes, and/or porosity, and/or space weathering, that is, the presence of more or less fresh material. The OSIRIS-REx mission primary sampling site, Nightingale, and a boulder known as the Roc, are redder than the background surface.
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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 | 0.001 | 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) | 0.003 | 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".