On the Relation between the Astronomical and Visual Photometric Systems in Specifying the Brightness of the Night Sky for Mesopically Adapted Observers
Bibliographic record
Abstract
Due to the typical ambient light levels in inhabited places and light pollution of the night sky, most naked-eye astronomical observations are performed nowadays under mesopic conditions. The luminance (cd/m2) associated with the brightness of the night sky specified in the astronomical logarithmic scale of magnitudes per square arcsecond (mag/arcsec2) is strongly dependent on the spectrum of the sky, because the spectral sensitivity of the human visual system is not coincident with the standard photometric bands used in astronomy. The conversion between these two families of photometric systems was previously analyzed for observers presumed to be either fully photopically or scotopically adapted. In this work, we deduce the transformation equations between the astronomical and visual photometric systems for specifying and reporting the sky brightness in the mesopic range, within the framework of the MES-2 system for visual performance-based mesopic photometry. It is shown that the dependence of the conversion factors on the correlated color temperature of the night sky reaches a minimum spread for adaptation luminances of 0.5–1.0 cd/m2. The sky luminances corresponding to 22.0 mag/arcsec2 in the Johnson-Cousins V band (the assumed brightness of a natural night sky devoid of light pollution) span, for 1.0 cd/m2 adaptation, a relatively small range of ~195–215 μcd/m2 in the absolute (AB) magnitude system and ~210–225 μcd/m2 in the Vega-referenced one.
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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 | 0.001 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".