PHYSICAL CHARACTERIZATION OF ∼2 m DIAMETER NEAR-EARTH ASTEROID 2015 TC25: A POSSIBLE BOULDER FROM E-TYPE ASTEROID (44) NYSA
Bibliographic record
Abstract
ABSTRACT Small near-Earth asteroids (NEAs) (<20 m) are interesting, because they are progenitors for meteorites in our terrestrial collection. The physical characteristics of these small NEAs are crucial to our understanding of the effectiveness of our atmosphere in filtering low-strength impactors. In the past, the characterization of small NEAs has been a challenge, because of the difficulty in detecting them prior to close Earth flyby. In this study, we physically characterized the 2 m diameter NEA 2015 TC25 using ground-based optical, near-infrared and radar assets during a close flyby of the Earth (distance 128,000 km) in 2015 October 12. Our observations suggest that its surface composition is similar to aubrites, a rare class of high-albedo differentiated meteorites. Aubrites make up only 0.14% of all known meteorites in our terrestrial meteorite collection. 2015 TC25 is also a very fast rotator with a period of 133 ± 6 s. We combined the spectral and dynamical properties of 2015 TC25 and found the best candidate source body in the inner main belt to be the 70 km diameter E-type asteroid (44) Nysa. We attribute the difference in spectral slope between the two objects to the lack of regolith on the surface of 2015 TC25. Using the albedo of E-type asteroids (50%–60%) we refine the diameter of 2015 TC25 to 2 m, making it one of the smallest NEAs ever to be characterized.
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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) | 0.001 | 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".