Design of a precision calibration unit for Keck NIRC2 AO instrument
Why this work is in the frame
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Bibliographic record
Abstract
High-precision astrometry has the potential to address questions in planet formation, black hole science, Galactic structure, and more. However, in order to achieve a precision of sub-milli arcseconds (mas), we need a calibration method better than the current techniques such as on-sky calibration using calibrated stellar or stellar cluster systems, which have a precision of $sim$ 1 mas. Precision calibration unit with a regular grid of photo-lithographically manufactured pinholes combined with self-calibration techniques, on the other hand, is a new and innovative way to potentially achieve a precision of sub-mas over the entire field of view. This technique is beneficial to adaptive optic (AO) instruments for future telescopes like the Thirty Meter Telescope (TMT). In this work, we present our design for a new astrometric calibration unit to feed the NIRC2 AO instrument at the W. M. Keck Observatory. It allows calibration over a large field of view of $47^{''} times 47^{''}$, spat
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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 | 0.000 | 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 it