A study of the high-inclination population in the Kuiper belt – IV. High-order mean-motion resonances in the classical region
Bibliographic record
Abstract
ABSTRACT In our previous study of Neptune’s 4:7 mean-motion resonance (MMR), we discovered that its resonant angle can only librate within a specific eccentricity (e) versus inclination (i) region, determined by a theoretical limiting curve. This ‘permissible region’ is independent of time and encompasses the entire possible stable region. We now generalize this theory to investigate all high-order MMRs embedded in the main classical Kuiper belt (MCKB). We first consider the second-order 3:5 MMR in the framework of planet migration and resonance capture, and have further validated our limiting curve theory for both captured and observed 3:5 resonators. It suggests that only the (e, i) pairs inside the individual permissible regions should be chosen as initial conditions for studying the in situ evolution of high-order resonators. With such a new setting, we proceed to explore the long-term stability (for 4 Gyr) of different resonant populations, and our simulations predict that (1) the 3:5 and 4:7 resonators are comparable in number, and they could have inclinations up to 40°, (2) the populations of objects in the higher order 5:9, 6:11, 7:12, and 7:13 resonances are about 1/10 of the 3:5 (or 4:7) resonator population, and nearly all of them are found on the less inclined orbits with i < 10°, and (3) for these high-order resonances, almost all resonators reside in their individual permissible regions. In summary, our results make predictions for the number and orbital distributions of potential resonant objects that will be discovered in the future throughout the MCKB.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".