The Resonant Transneptunian Populations
Bibliographic record
Abstract
The transneptunian objects (TNOs) trapped in mean-motion resonances with Neptune were likely emplaced there during planet migration late in the giant-planet formation process. We perform detailed modelling of the resonant objects detected in the Canada-France Ecliptic Plane Survey (CFEPS) in order to provide population estimates and, for some resonances, constrain the complex internal orbital element distribution. Detection biases play a critical role because phase relationships with Neptune make object discovery more likely at certain longitudes. This paper discusses the 3:2, 5:2, 2:1, 3:1, 5:1, 4:3, 5:3, 7:3, 5:4, and 7:4 mean-motion resonances, all of which had CFEPS detections, along with our upper limit on 1:1 Neptune Trojans (which is consistent with their small population estimated elsewhere). For the plutinos (TNOs in the 3:2 resonance) we refine the orbital element distribution given in Kavelaars et al. (2009) and show that steep H-magnitude distributions (N(H) proportional to 10aH, with a=0.8-0.9) are favoured in the range Hg=8-9, and confirm that this resonance does not share the inclination distribution of the classical Kuiper Belt. We give the first population estimate for the 5:2 resonance and find that, to within the uncertainties, the population is equal to that of the 3:2 (13,000 TNOs with Hg < 9.16), whereas the 2:1 population is smaller by a factor of 3-4 compared to the other two resonances. We also measure significant populations inhabiting the 4:3, 5:3, 7:3, 5:4, 7:4, 3:1, and 5:1 resonances, with Hg < 9.16 (D >100 km) populations in the thousands. We compare our intrinsic population and orbital-element distributions with several published models of resonant-TNO production; the most striking discrepancy is that resonances beyond the 2:1 are in reality more heavily populated than in published models.
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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 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".