Hydrogen abundance estimation and distribution on (101955) Bennu
Bibliographic record
Abstract
Asteroids were likely a major source of volatiles and water to early Earth. Quantifying the hydration of asteroids is necessary to constrain models of the formation and evolution of the Solar System and the origin of Life on Earth. The OSIRIS-REx (Origins, Spectral Interpretation, Resource Identification, and Security–Regolith Explorer) mission showed that near-Earth asteroid (101955) Bennu contains widespread, abundant hydrated phyllosilicates , indicated by a ubiquitous absorption at ~ 2.7 μm. The objective of this work is to quantify the hydration—that is, the hydrogen content—of phyllosilicates on Bennu's surface and investigate how this hydration varies spatially. We analyse spectral parameters (normalized optical path length, NOPL; effective single-scattering albedo , ESPAT; and Gaussian modeling) computed from the hydrated phyllosilicate absorption band of spatially resolved visible–near-infrared spectra acquired by OVIRS (the OSIRIS-REx Visible and InfraRed Spectrometer). We also computed the same spectral parameters using laboratory-measured spectra of meteorites including CMs, CIs, and the ungrouped C2 Tagish Lake. We estimate the mean hydrogen content of water and hydroxyl groups in hydrated phyllosilicates on Bennu's surface to be 0.71 ± 0.16 wt%. This value is consistent with the hydration range of some aqueously altered meteorites (CMs, C2 Tagish Lake), but not the most aqueously altered group (CIs). The sample collection site of the OSIRIS-REx mission has slightly higher hydrogen content than average. Spatial variations in hydrogen content on Bennu's surface are linked to geomorphology , and may have been partially inherited from its parent body.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".