Exploring Variability within the Col-OSSOS Sample
Bibliographic record
Abstract
Beyond the orbit of Neptune lies a sea of small icy bodies known as the Kuiper belt. The surfaces of these Kuiper Belt Objects (KBOs) have remained relatively unprocessed since their formation as a consequence of their distance from the Sun. This means that we can investigate their formation conditions in the early Solar System by studying their surfaces today. Generally, the small and most numerous KBOs are quite dim (r mag > 22), and so it is difficult to study their surfaces spectroscopically. Instead, we can use broadband photometry to take effectively very low-resolution spectra of their surfaces. When studied spectroscopically, the surfaces of smaller KBOs have generally shown very flat and featureless spectra within certain wavelength ranges. This means that broadband photometry (within those wavelength ranges) can reveal enough information to characterise the optical and near-infrared spectral slopes of these planetesimals. The Colours of the Outer Solar System Origins Survey (Col-OSSOS) has obtained optical and near-infrared broadband photometry of a sample of 92 KBOs, at unprecedented precision (~ ±0.03 mag in optical wavelengths). These broadband surface colours allow small, dynamically excited KBOs to be characterised into a bimodal colour distribution (as with previous colour surveys), along with the identification of potentially outlying surface colours. As a side effect of Col-OSSOS’s observing technique we have a sample of objects with repeated optical colours, and some repeated near-infrared colours. We also have taken additional optical photometry of a small sample of KBOs with outlying surface colours. This allows us to investigate the possibility of photometric variation across multiple epochs for this sample of objects. Col-OSSOS observed sequential broadband filters on timescales less than the typical periods of small KBOs. Therefore, we can simultaneously fit a linear lightcurve and photometric colours to our photometry and potentially rule out lightcurve effects causing photometric variations. This means that differing colours across multiple epochs implies either differing surface composition, or that our approximation of linear brightness variability across the observing sequence is invalidated. We will present this sample and discuss implications for the spectrovariable population within the Kuiper belt.
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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 | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 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) | 0.003 | 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".