Olivine‐rich exposures at Bellicia and Arruntia craters on (4) Vesta from Dawn <scp>FC</scp>
Bibliographic record
Abstract
Abstract We present an analysis of olivine‐rich exposures at Bellicia and Arruntia craters using Dawn Framing Camera (FC) color data. Our results confirm the existence of olivine‐rich materials at these localities as described by Ammannito et al. ( ) using Visual Infrared Spectrometer (VIR) data. Analyzing laboratory spectra of various howardite–eucrite–diogenite meteorites, high‐Ca pyroxenes, olivines, and olivine‐orthopyroxene mixtures, we derive three FC spectral band parameters that are indicators of olivine‐rich materials. Combining the three band parameters allows us, for the first time, to reliably identify sites showing modal olivine contents >40%. The olivine‐rich exposures at Bellicia and Arruntia are mapped using higher spatial resolution FC data. The exposures are located on the slopes of outer/inner crater walls, on the floor of Arruntia, in the ejecta, as well as in nearby fresh small impact craters. The spatial extent of the exposures ranges from a few hundred meters to few kilometers. The olivine‐rich exposures are in accordance with both the magma ocean and the serial magmatism model (e.g., Righter and Drake ; Yamaguchi et al. ). However, it remains unsolved why the olivine‐rich materials are mainly concentrated in the northern hemisphere (approximately 36–42°N, 46–74°E) and are almost absent in the Rheasilvia basin.
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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 | 0.000 | 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) | 0.002 | 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".