OSSOS. VIII. The Transition between Two Size Distribution Slopes in the Scattering Disk
Bibliographic record
Abstract
Abstract The scattering trans-Neptunian Objects (TNOs) can be measured to smaller sizes than any other distant small-body population. We use the largest sample yet obtained, 68 discoveries, primarily by the Outer Solar System Origins Survey (OSSOS), to constrain the slope of its luminosity distribution, with sensitivity to much fainter absolute H-magnitudes than previous work. Using the analysis technique in Shankman et al., we confirm that a single slope for the H-distribution is not an accurate representation of the scattering TNOs and Centaurs, and that a break in the distribution is required, in support of previous conclusions. A bright-end slope of α b = 0.9 transitioning to a faint-end slope α f of 0.4–0.5 with a differential number contrast c from 1 (a knee) to 10 (a divot) provides an acceptable match to our data. We find that break magnitudes H b of 7.7 and 8.3, values both previously suggested for dynamically hot Kuiper Belt populations, are equally non-rejectable for a range of α f and c in our statistical analysis. Our preferred divot H-distribution transitions to α f = 0.5 with a divot of contrast c = 3 at H b = 8.3, while our preferred knee H-distribution transitions to α f = 0.4 at H b = 7.7. The intrinsic population of scattering TNOs required to match the OSSOS detections is 3 × 106 for H r < 12, and 9 × 104 for H r < 8.66 (D ≳ 100 km), with Centaurs having an intrinsic population two orders of magnitude smaller.
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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 | 0.000 |
| 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) | 0.001 | 0.000 |
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".