OSSOS. XIX. Testing Early Solar System Dynamical Models Using OSSOS Centaur Detections
Bibliographic record
Abstract
Abstract We use published models of the early solar system evolution with a slow, long-range and grainy migration of Neptune to predict the orbital element distributions and the number of modern-day Centaurs. The model distributions are biased by the Outer Solar System Origins Survey (OSSOS) simulator and compared with the OSSOS Centaur detections. We find an excellent match to the observed orbital distribution, including the wide range of orbital inclinations which was the most troublesome characteristic to fit in previous models. A dynamical model, in which the original population of outer disk planetesimals was calibrated from Jupiter trojans, is used to predict that OSSOS should detect 11 ± 4 Centaurs with semimajor axes of a < 30 au, perihelion distances of q > 7.5 au, and diameter of D > 10 km (absolute magnitude H r < 13.7 for a 6% albedo). This is consistent with 15 actual OSSOS Centaur detections with H r < 13.7. The population of Centaurs is estimated to be 21,000 ± 8000 for D > 10 km. The inner scattered disk at 50 < a < 200 au should contain (2.0 ± 0.8) × 10 7 D > 10 km bodies and the Oort cloud should contain (5.0 ± 1.9) × 10 8 D > 10 km comets. Population estimates for different diameter cutoffs can be obtained from the size distribution of Jupiter trojans ( N (> D ) ∝ D −2.1 for 5 < D < 100 km). We discuss model predictions for the Large Synoptic Survey Telescope observations of Centaurs.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| 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".