Sky Quality Meter measurements in a colour-changing world
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
The Sky Quality Meter (SQM) has become the most common device used to track the evolution of the brightness of the sky from polluted regions to first-class astronomical observatories. A vast database of SQM measurements already exists for many places in the world. Unfortunately, the SQM operates over a wide spectral band and its spectral response interacts with the sky's spectrum in a complex manner. This is why the optical signals are difficult to interpret when the data are recorded in regions with different sources of artificial light. The brightness of the night sky is linked in a complex way to ground-based light emissions, while taking into account atmospheric-induced optical distortion as well as spectral transformation from the underlying ground surfaces. While the spectral modulation of the sky's radiance has been recognized, it still remains poorly characterized and quantified. The impact of the SQM's spectral characteristics on sky-brightness measurements is analysed here for different light sources, including low- and high-pressure sodium lamps, PC-amber and white LEDs, metal halide and mercury lamps. We show that a routine conversion of radiance to magnitude is difficult, or rather impossible, because the average wavelength depends on actual atmospheric and environment conditions, the spectrum of the source and device-specific properties. We correlate SQM readings with both the Johnson astronomical photometry bands and the human system of visual perception, assuming different lighting technologies. These findings have direct implications for the processing of SQM data and for their improvement and/or remediation.
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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 | 0.001 | 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 | 0.001 | 0.001 |
| 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 it