HYPERCALIBRATION: A PAN-STARRS1-BASED RECALIBRATION OF THE SLOAN DIGITAL SKY SURVEY PHOTOMETRY
Bibliographic record
Abstract
ABSTRACT We present a recalibration of the Sloan Digital Sky Survey (SDSS) photometry with new flat fields and zero points derived from Pan-STARRS1. Using point-spread function (PSF) photometry of 60 million stars with 16 < r < 20, we derive a model of amplifier gain and flat-field corrections with per-run rms residuals of 3 millimagnitudes (mmag) in griz bands and 15 mmag in u band. The new photometric zero points are adjusted to leave the median in the Galactic north unchanged for compatibility with previous SDSS work. We also identify transient non-photometric periods in SDSS (“contrails”) based on photometric deviations co-temporal in SDSS bands. The recalibrated stellar PSF photometry of SDSS and PS1 has an rms difference of {9, 7, 7, 8} mmag in griz , respectively, when averaged over 15′ regions.
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".