The SCUBA Legacy Catalogues: Submillimeter‐Continuum Objects Detected by SCUBA
Bibliographic record
Abstract
We present the SCUBA Legacy Catalogues, two comprehensive sets of continuum maps (and catalogs) using data at 850 and 450 μm of the various astronomical objects obtained with the Submillimetre Common User Bolometer Array (SCUBA). The Fundamental Map Data Set contains data only where superior atmospheric opacity calibration data were available. The Extended Map Data Set contains data regardless of the quality of the opacity calibration. Each data set contains 1.2° × 1.2° maps at locations where data existed in the JCMT archive, imaged using the matrix inversion method. The Fundamental Data Set is composed of 1423 maps at 850 μm and 1357 maps at 450 μm. The Extended Data Set is composed of 1547 maps at 850 μm. Neither data set includes high sensitivity, single-chop SCUBA maps of "cosmological fields" nor solar system objects. Each data set was used to determine a respective object catalogue, consisting of objects identified within the respective 850 μm maps using an automated identification algorithm. The Fundamental and Extended Map Object Catalogues contain 5061 and 6118 objects, respectively. Objects are named based on their respective J2000.0 position of peak 850 μm intensity. The catalogues provide for each object the respective maximum 850 μm intensity, estimates of total 850 μm flux and size, and tentative identifications from the SIMBAD Database. Where possible, the catalogues also provide for each object its maximum 450 μm intensity and total 450 μm flux and flux ratios.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.008 | 0.010 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.051 | 0.063 |
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".