Col-OSSOS: The Colors of the Outer Solar System Origins Survey
Bibliographic record
Abstract
Abstract The Colours of the Outer Solar System Origins Survey is acquiring near-simultaneous g, r, and J photometry of unprecedented precision with the Gemini North Telescope, targeting nearly 100 trans-Neptunian objects (TNOs) brighter than m r = 23.6 mag discovered in the Outer Solar System Origins Survey. Combining the optical and near-infrared photometry with the well-characterized detection efficiency of the Colours of the Outer Solar System Origins Survey target sample will provide the first flux-limited compositional dynamical map of the outer solar system. In this paper, we describe our observing strategy and detail the data reduction processes we employ, including techniques to mitigate the impact of rotational variability. We present optical and near-infrared colors for 35 TNOs. We find two taxonomic groups for the dynamically excited TNOs, the neutral and red classes, which divide at g − r ≃ 0.75. Based on simple albedo and orbital distribution assumptions, we find that the neutral class outnumbers the red class, with a ratio of 4:1 and potentially as high as 11:1. Including in our analysis constraints from the cold classical objects, which are known to exhibit unique albedos and r − z colors, we find that within our measurement uncertainty our observations are consistent with the primordial solar system protoplanetesimal disk being neutral class dominated, with two major compositional divisions in grJ color space.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| 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) | 0.011 | 0.005 |
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".