Regional Photometric Modeling of Asteroid (101955) Bennu
Bibliographic record
Abstract
Abstract We present a regional photometric analysis of asteroid (101955) Bennu, using image data from the MapCam color imager of the OSIRIS-REx Camera Suite (OCAMS). This analysis follows the previously reported global photometric analysis of Bennu, which found that Bennu’s roughness was difficult to photometrically model owing to unresolved surface variation. Here we find that, even with a high-resolution shape model (20 cm per facet) and automatic image registration (<1 pixel error), Bennu remains a challenging surface to photometrically model: neither a suite of empirical photometric models nor the physically motivated Hapke model were able to eliminate the scatter in the data due to pixel-scale variations. Nonetheless, the models improved on the global analysis by identifying regional variations in Bennu’s photometric response. A linear empirical model, when compared with independent measures of surface roughness and albedo, revealed correlations between those characteristics and phase slope. A regional Hapke analysis showed the same structure in its single-scattering albedo and asymmetry factors; although the Hapke parameters were loosely constrained, complicating interpretation of their spatial variation, the regional variation in relative parameter sensitivity also correlated with shallower phase slope, higher albedo, and less macroscopic roughness.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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 teacher head, 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".