Properties of the Trans-Neptunian Belt: Statistics From the CFHT Survey
Bibliographic record
Abstract
We present the results of a wide-field survey designed to measure the size, inclination, and radial distributions of Kuiper Belt Objects (KBOs). The survey found 86 KBOs in 73 square degrees observed to limiting red magnitude 23.7 using the Canada-France-Hawaii Telescope and the 12k x 8k CCD Mosaic camera. For the first time, both ecliptic and off-ecliptic fields were examined to more accurately constrain the inclination distribution of the KBOs. The survey data were processed using an automatic moving object detection algorithm, allowing a careful characterization of the biases involved. In this work, we quantify fundamental parameters of the Classical KBOs (CKBOs), the most numerous objects found in our sample, using the new data and a maximum likelihood simulation. Deriving results from our best-fit model, we find that the size distribution follows a differential power law with exponent q = 4.0 (+0.6)(-0.5) (1 sigma, or 68.27% confidence). In addition, the CKBOs inhabit a very thick disk consistent with a Gaussian distribution of inclinations with a Half-Width of i(1/2) = 20 (+6)(-4) deg (1 sigma). We estimate that there are N = 3.8 (+2.0)(-1.5) x 10^4 (1 sigma) CKBOs larger than 100 km in diameter. We also find compelling evidence for an outer edge to the CKBOs at heliocentric distance R = 50 AU.
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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 | 0.002 | 0.002 |
| 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".