A CAREFULLY CHARACTERIZED AND TRACKED TRANS-NEPTUNIAN SURVEY: THE SIZE DISTRIBUTION OF THE PLUTINOS AND THE NUMBER OF NEPTUNIAN TROJANS
Bibliographic record
Abstract
ABSTRACT The trans-Neptunian objects (TNOs) preserve evidence of planet building processes in their orbital and size distributions. While all populations show steep size distributions for large objects, a relative deficit of Neptunian trojans and scattering objects with diameters of D < 100 km has been detected. We investigated this deficit with a 32 square degree survey, in which we detected 77 TNOs that are brighter than a limiting r-band magnitude of 24.6. Our plutino sample (18 objects in 3:2 mean-motion resonance with Neptune) shows a deficit of D < 100 km objects, rejecting a single power-law size distribution at >99% confidence. Combining our survey with the Canada–France Ecliptic Plane Survey, we perform a detailed analysis of the allowable parameters for the plutino size distribution, including knees and divots. We surmise the existence of 9000 ± 3000 plutinos with an absolute magnitude of H r ≤ 8.66 and with H r ≤ 10.0 (95% confidence). Our survey also discovered one temporary Uranian trojan, one temporary Neptunian trojan, and one stable Neptunian trojan, for which we estimate populations of , , and with H r ≤ 10.0, respectively. All three populations are thus less numerous than the main belt asteroids (592 asteroids with H r ≤ 10.0). With such population sizes, the temporary Neptunian trojans cannot be previously stable trojans diffusing out of the resonance now; they must be recently captured Centaurs or scattering objects. As the bias against the detection of objects grows with larger semimajor axes, our discovery of three 3:1 resonators and one 4:1 resonator adds to the growing evidence that the high-order resonances are far more populated than is typically predicted.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".