The Thousand Asteroid Light Curve Survey
Bibliographic record
Abstract
We present the results of our Thousand Asteroid Light Curve Survey (TALCS) conducted with the Canada-France-Hawaii Telescope in September 2006. Our untargeted survey detected 828 Main Belt asteroids to a limiting magnitude of g'~22.5 corresponding to a diameter range of 0.4 km <= D <= 10 km. Of these, 278 objects had photometry of sufficient quality to perform rotation period fits. We debiased the observations and light curve fitting process to determine the true distribution of rotation periods and light curve amplitudes of Main Belt asteroids. We confirm a previously reported excess in the fraction of fast rotators but find a much larger excess of slow rotating asteroids (~15% of our sample). A few percent of objects in the TALCS size range have large light curve amplitudes of ~1 mag. Fits to the debiased distribution of light curve amplitudes indicate that the distribution of triaxial ellipsoid asteroid shapes is proportional to the square of the axis-ratio, (b/a)^2, and may be bi-modal. Finally, we find six objects with rotation periods that may be less than 2 hours with diameters between 400 m and 1.5 km, well above the break-up limit for a gravitationally-bound aggregate. Our debiased data indicate that this population represents <4% of the Main Belt in the 1-10 km size range.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".