Search and study for meteorites analogous to Didymos
Bibliographic record
Abstract
ABSTRACT The Hera mission will arrive at the Didymos system to study the efficiency of momentum transfer and to further investigate the binary system in great detail after the Double Asteroid Redirection Test (DART) mission impact. We took advantage of two online data bases of meteorites spectra and of recent Didymos spectra taken before and after the DART impact. We performed the first selection based on the comparison of the band centre values of the silicate absorption bands (localized at 1 and 2 μm) between Didymos and the meteorites. The second selection was made defining a four-dimensional space parameter whose dimensions were the band depth and the slope of the two bands, normalized to Didymos values. We introduced a distance measure to find the closest meteorites to Didymos in this space. Finally, we made the last selection based on other criteria, such as the presence of different spectra of the same meteorite, the presence of different spectra from different data bases, and the comparison with the literature. The result of this work is a list of six meteorites that are the most analogous to Didymos system. We also found out that Didymos is most probably mainly composed of L/LL ordinary chondrites, with a preference for the LL sub-type. From our list of meteorites, we were able to estimate the normalized abundance of olivine and pyroxene of Didymos. Finally, a match between Didymos and OC meteorites was also found in the Mid-InfraRed (MIR) range.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".