Rotation Periods of Asteroids Determined With Bootstrap Convex Inversion From ATLAS Photometry
Bibliographic record
Abstract
The rotation period is one of the fundamental physical characteristics of asteroids. It can be determined from photometric measurements by standard methods of time-series period analysis or by creating a physical model of an asteroid with the rotation period being one of the fitted parameters. We used the latter approach to determine the sidereal rotation period for more than 5000 asteroids, out of which about 1600 are those for which their period was not known. We processed photometric measurements of about 100,000 asteroids from the ATLAS survey with the light curve inversion technique in the Asteroids@home project to search for the best-fit rotation period. This was repeated 25 times with randomly resampled—bootstrapped—data. For thousands of asteroids, their best-fit period was the same for most of the bootstrapped data sets; thus, their rotation period was determined with a high degree of reliability.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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".