Col-OSSOS: z-Band Photometry Reveals Three Distinct TNO Surface Types
Bibliographic record
Abstract
Abstract Several different classes of trans-Neptunian objects (TNOs) have been identified based on their optical and near-infrared colors. As part of the Colours of the Outer Solar System Origins Survey (Col-OSSOS), we have obtained g-, r-, and z-band photometry of 26 TNOs using Subaru and Gemini Observatories. Previous color surveys have not utilized z-band reflectance, and the inclusion of this band reveals significant surface reflectance variations between sub-populations. The colors of TNOs in g − r and r − z show obvious structure, and appear consistent with the previously measured bi-modality in g − r. The distribution of colors of the two dynamically excited surface types can be modeled using the two-component mixing models from Fraser & Brown. With the combination of g − r and r − z, the dynamically excited classes can be separated cleanly into red and neutral surface classes. In g − r and r − z, the two dynamically excited surface groups are also clearly distinct from the cold classical TNO surfaces, which are red, with and r − z ≲ 0.6, while all dynamically excited objects with similar g − r colors exhibit redder r − z colors. The z-band photometry makes it possible for the first time to differentiate the red excited TNO surfaces from the red cold classical TNO surfaces. The discovery of different r − z colors for these cold classical TNOs makes it possible to search for cold classical surfaces in other regions of the Kuiper Belt and to completely separate cold classical TNOs from the dynamically excited population, which overlaps in orbital parameter space.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".