An AzTEC 1.1 mm survey of the GOODS-N field - I. Maps, catalogue and source statistics
Bibliographic record
Abstract
We have conducted a deep and uniform 1.1 mm survey of the Great Observatories Origins Deep Survey-North (GOODS-N) field with AzTEC on the James Clerk Maxwell Telescope. Here, we present the first results from this survey including maps, the source catalogue and 1.1 mm number counts. The results presented here were obtained from a 245 arcmin2 region with a near uniform coverage to a depth of 0.96–1.16 mJy beam−1. Our robust catalogue contains 28 source candidates detected with S/N ≥ 3.75, only ∼1– 2 of which are expected to be spurious detections. Of these source candidates, eight are also detected by Submillimetre Common-User Bolometer Array (SCUBA) at 850 μm in regions where there is a good overlap between the two surveys. The major advantage of our survey over that with SCUBA is the uniformity of coverage. We calculate number counts using two different techniques: the first using a frequentist parameter estimation and the second using a Bayesian method. The two sets of results are in good agreement. We find that the 1.1 mm differential number counts are well described in the 2–6 mJy range by the functional form dN/dS=N′(S′/S) exp(−S/S′) with fitted parameters S′= 1.25 ± 0.38 mJy and dN/dS= 300 ± 90 mJy−1deg−2 at 3 mJy.
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How this classification was reachedexpand
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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".