Spectral effects of varying texture and composition in two‐component “mudpie” simulations: Insights for asteroid (101955) Bennu
Bibliographic record
Abstract
Abstract Data returned by the OSIRIS‐REx (Origins, Spectral Interpretation, Resource Identification, and Security–Regolith Explorer) spacecraft have shown that asteroid (101955) Bennu has a globally low‐albedo surface covered in boulders with diverse texture, color, and albedo properties, and an aqueously altered composition dominated by phyllosilicates. To test whether Bennu’s color and albedo diversity could be caused by texture and/or composition variations, we performed a laboratory‐based study using simple two‐component mixtures (called “mudpies”) of the phyllosilicate saponite and carbon‐rich opaques. Each mudpie is prepared in four different textures: fine powder, coarse particles, sanded slab, and textured rock. We find that a sanded slab made from 90% saponite and 10% lampblack is a good analog for Bennu, and the color and albedo changes due to texture variations are substantial. At 550 nm, texture changes alone can create up to 36% brightness contrast, and in color measured as a 473 nm/847 nm ratio, texture changes can provide up to 18% color contrast. In comparison, Bennu shows approximately 25% albedo and <1% color contrasts from boulder type to boulder type. These findings suggest that if texture contributes to color on Bennu, the texture variations are typically more subtle than what we simulated in the laboratory. According to our study, the color and albedo properties of different boulder types on Bennu are consistent with different concentrations of carbon‐rich opaques (and possibly consistent with variations in carbonate concentration). The variations within each boulder group are consistent with textural differences.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.001 |
| 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".