High-cadence light curves for bright TNOs in CLASSY
Bibliographic record
Abstract
The Classical and Large-A distant Solar SYstem Survey (CLASSY) is a deep TransNeptunian Object (TNO) search using the MegaPrime camera on the Canada-France-Hawaii Telescope. During one of its observing runs in the summer of 2022, a fortuitous confluence of circumstance resulted in one of the search fields receiving nine nearly consecutive nights of data, each containing 3-4 hours of imaging data of 5-minute exposures. This unusually dense cadence provides an excellent data set to look for variability in the outer Solar System objects that happen to be in the field. In this thesis, we report the results of an examination of the brightest TNO in the field (the previously known TNO 2001 OK108 with no published light-curve study) and have studied its photometric time series to determine its rotational properties. The data supports a double-peaked light curve of a peak-to-peak magnitude of 0.23 mag and a rotational period of 17.8±0.5 hours. We have also studied the rotational variability of the brightest TNO in the JF block of CLASSY called JF2035. Our data indicates that this object has a rotational period of 7.15±0.04 hours and a peak-to-peak magnitude of 0.16 mag. If the rotations are being viewed in an edge-on geometry, a model with a triaxial body in principle axis rotation implies long to intermediate axis ratios of 1.22 and 1.13, respectively, with larger ratios required if the viewing geometry approaches pole-on.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.003 | 0.001 |
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".