Astrometry with MCAO: HST-GeMS proper motions in the globular cluster NGC 6681
Bibliographic record
Abstract
\n Aims. For the first time the astrometric capabilities of the Gemini Multi-Conjugate Adaptive Optics System (GeMS) facility at the Gemini South Adaptive Optics Imager (GSAOI) camera on Gemini-South are tested to quantify the accuracy in determining stellar proper motions in the Galactic globular cluster NGC 6681. \n Methods. Proper motions from the Hubble Space Telescope (HST) for a sample of its stars are already available, allowing us to construct a distortion-free reference at the epoch of GeMS observations that is used to measure and correct the temporally changing distortions for each GeMS exposure. In this way, we are able to compare the corrected GeMS images with a first-epoch of HST-Advanced Camera for Survey (ACS) images to recover the relative proper motion of the Sagittarius dwarf spheroidal galaxy with respect to NGC 6681.\n Results. We find this to be (μαcosδ,μδ) = (4.09,−3.41)mas yr-1, which matches previous HST/ACS measurements with a very good accuracy of 0.03 mas yr-1 and with a comparable precision (rms of 0.43 mas yr-1).\n Conclusions. This study successfully demonstrates that high-quality proper motions can be measured for relatively large fields of view (85′′× 85′′) with MCAO-assisted, ground-based cameras and provides a first, successful test of the performances of GeMS on multi-epoch data. \n
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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 | 0.000 | 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 | 0.001 |
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".