JHK standard stars for large telescopes: the UKIRT Fundamental and Extended lists
Bibliographic record
Abstract
We present high-precision JHK photometry with the 3.8-m UK Infrared Telescope (UKIRT) of 82 standard stars, 28 from the widely used preliminary list known as the ‘UKIRT Faint Standards’, referred to here as the Fundamental List, and 54 additional stars referred to as the Extended List. The stars have 9.4<K<15.0 and all or most should be readily observable with imaging array detectors in normal operating modes on telescopes of up to 10-m aperture. Many are accessible from the southern hemisphere. Arcsec-accuracy positions (J2000, epoch ∼1998) are given, together with optical photometry and spectral types from the literature, where available, or inferred from the J−K colour. K-band finding charts are provided for stars with proper motions exceeding 0.3 arcsec yr−1. We discuss some pitfalls in the construction of flat-fields for array imagers and a method to avoid them. On 30 nights between late 1994 and early 1998 the stars from the Fundamental List, which were used as standards for the whole programme, were observed on an average of 10 nights each, and those from the Extended List on an average of six nights. The average internal standard error of the mean results for the K magnitudes is 0.005 mag; for the J−H colours it is 0.003 mag for the Fundamental List stars and 0.005 mag for those of the Extended List; for H−K the average is 0.004 mag. The results are on the natural system of the IRCAM3 imager, which used a 256×256 InSb detector array with ‘standard’JHK filters, behind gold-coated fore-optics and a gold- or silver-dielectric coated dichroic. We give colour transformations on to the CIT, Arcetri and LCO/Palomar NICMOS systems, and preliminary transformations on to the system defined by the new Mauna Kea Observatory near-infrared filter set.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.016 | 0.010 |
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".