A GCs search in M31 with Gaia, PS1, LAMOST, PAndAS (Wang+, 2023)
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 Panoramic Survey Telescope and Rapid Response System (Pan-STARRS), located at Hawaii, conducted a stacked 3{pi} Steradian Survey in the five broad bands grizy_p1_. We used the PSF magnitude of grizyp1 and the colors (g-r, r-i, i-y, and y-z). See Section 2.1. We used the classification data in the Low-Resolution Spectroscopic (LRS) Survey of the Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST) DR8 as auxiliary data in Sections 3.1 and 4.2. LAMOST, also called the Guo Shou Jing Telescope, is a specially designed Schmidt telescope with both a large aperture (an effective aperture of 3.6-4.9m) and a wide field of view (5{deg}). It is capable of observing thousands of targets using 4000 fibers in a single observation. The spectrum wavelength coverage is from 370 to 900nm, with a resolving power of ~1800. We used a subsample of LAMOST DR8 LRS that had a signal-to-noise ratio (S/N) larger than 20. To avoid contamination from M31, we excluded the sources in a 3.5{deg}x3.5{deg} area centered at M31. see Section 2.3. Our visual inspection relies on the optical images of the PAndAS survey, which were obtained around M31 and M33 by the Canada-France-Hawaii Telescope, with average seeings of 0.6" and 0.67" in the i and g bands, respectively. See Section 2.4.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.009 | 0.008 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.001 | 0.005 |
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