Discovering and securing TNOs: the CFHTLS Ecliptic survey
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
We have developed an international collaboration aimed at discovering and long-term tracking of a large Trans-Neptunian Object (TNO) sample. The scientific rationale behind this extended observational effort is to understand the dynamical structure of the outer Solar System. This structure provides a unique tracer of planetary accretion processes and constrains models of formation and early evolution of our outer Solar System. Our observational program is designed to first discover a large sample of TNOs in well characterized surveys and then track them in a manner which will avoid what we call ‘follow-up bias’. We first briefly describe the current status of our current observational knowledge of the Kuiper Belt. Next we show how following-up almost all objects discovered in a survey has changed our view of the dynamical structure of the Kuiper Belt. Thanks to our work, previously empty places have been filled in, the relative importance of the then known dynamical population have been largely modified, and a new, potentially very large, population have been discovered. Discoveries presented in this paper were done at CFHT, while recoveries were performed on multiple telescopes, including in particular the ESO telescopes and the MPIA telescopes in Calar Alto (Spain). Finally, we briefly describe the ecliptic component of the CFHT Legacy Survey for which Kuiper Belt science is the main driver. Our experience with discovery and follow-up observations has led us to design an efficient time-sequence of observations for this survey.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it