PLUTINO DETECTION BIASES, INCLUDING THE KOZAI RESONANCE
Bibliographic record
Abstract
Because of their relative proximity within the trans-Neptunian region, the plutinos (objects in the 3:2 mean-motion resonance with Neptune) are numerous in flux-limited catalogs, and well-studied theoretically. We perform detailed modeling of the on-sky detection biases for plutinos, with special attention to those that are simultaneously in the Kozai resonance. In addition to the normal 3:2 resonant argument libration, Kozai plutinos also show periodic oscillations in eccentricity and inclination, coupled to the argument of perihelion (ω) oscillation. Due to the mean-motion resonance, plutinos avoid coming to pericenter near Neptune's current position in the ecliptic plane. Because Kozai plutinos are restricted to certain values of ω, perihelion always occurs out of the ecliptic plane, biasing ecliptic surveys against finding these objects. The observed Kozai plutino fraction has been measured by several surveys, finding values between 8% and 25%, while the true Kozai plutino fraction has been predicted to be between 10% and 30% by different giant planet migration simulations. We show that varies widely depending on the ecliptic latitude and longitude of the survey, so debiasing to find the true ratio is complex. Even a survey that covers most or all of the sky will detect an apparent Kozai fraction that is different from . We present a map of the on-sky plutino Kozai fraction that would be detected by all-sky flux-limited surveys. This will be especially important for the Panoramic Survey Telescope and Rapid Response System and Large Synoptic Survey Telescope projects, which may detect large numbers of plutinos as they sweep the sky. and the distribution of the orbital elements of Kozai plutinos may be a diagnostic of giant planet migration; future migration simulations should provide details on their resonant Kozai populations.
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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 | 0.002 |
| 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 | 0.001 | 0.001 |
| 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".