Evaluation of the Sky Brightness at Two Argentinian Astronomical Sites
Bibliographic record
Abstract
Light pollution is a growing concern at many levels, especially for the astronomical community. Indeed, not only does artificial lighting veil celestial objects, it disturbs the measurement of many atmospheric phenomena. The sky brightness is one of the most relevant parameters for astronomical site selection. Our goal is to evaluate the sky brightness of two Argentinian observation sites: LEO ++ and El Leoncito. Both sites were preselected to host the Cherenkov Telescope Array. This project consists of an arrangement of many telescopes that can measure high-energy gamma ray emissions via their Cherenkov radiation produced when entering the earth's atmosphere. In this paper, we describe the measurement methods used to determine whether those sites are valuable or not. We compared our results with the sky radiance of different renowned astronomical sites (Kitt Peak, Arizona, and Mont-Mégantic, Québec, Canada). Among our results, we found that LEO ++ is a good site, however the presence of a low layer of local aerosol can introduce uncertainties in the measurements. Consequently, El Leoncito would be a better option for such an installation. This latter site shows very low sky brightness levels, which are optimal for low light detection.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".