OSSOS. XXIX. The Population and Perihelion Distribution of the Detached Kuiper Belt
Bibliographic record
Abstract
The detached transneptunian objects (TNOs) are those with semimajor axes beyond the 2:1 resonance with Neptune, which are neither resonant nor scattering. Using the detached sample from the OSSOS telescopic survey, we produce the first studies of their orbital distribution based on matching the orbits and numbers of the known TNOs after accounting for survey biases. We show that the detached TNO perihelion ($q$) distribution cannot be uniform, but is instead better matched by two uniform components with a break near $q\approx40$ au. We produce parametric two-component models that are not rejectable by the OSSOS data set, and estimate that there are $36,\!000^{+12,000}_{-9,000}$ detached TNOs with absolute magnitudes $H_r < 8.66$ ($D \gtrsim 100$ km) and semimajor axes $48 < a < 250$ au (95% confidence limits). Although we believe these heuristic two-parameter models yield a correct population estimate, we then use the same methods to show that the perihelion distribution of a detached disk created by a simulated rogue planet matches the $q$ distribution even better, suggesting that the temporary presence of other planets in the early Solar System is a promising model to create today's large semimajor axis TNO population. This numerical model results in a detached TNO population estimate of $48,\!000^{+15,000}_{-12,000}$. Because this illustrates how difficult-to-detect $q>50$ au objects are likely present, we conclude that there are $(5 \pm 2)\times10^4$ dynamically detached TNOs, which are thus roughly twice as numerous as the entire transneptunian hot main 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 | 0.001 |
| 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) | 0.052 | 0.016 |
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".