First Constraints on Source Counts at 350 μm
Bibliographic record
Abstract
We have imaged a ~6 arcmin 2 region in the Boötes Deep Field using the 350 μm-optimized second-generation Submillimeter High Angular Resolution Camera (SHARC II), achieving a peak 1 σ sensitivity of ~5 mJy. We detect three sources above 3 σ, and determine a spurious source detection rate of 1.09 in our maps. In the absence of 5 σ detections, we rely on deep 24 μm and 20 cm imaging to deduce which sources are most likely to be genuine, giving two real sources. From this we derive an integral source count of 0.84 sources arcmin -2 at S > 13 mJy, which is consistent with 350 μm source count models that have an IR-luminous galaxy population evolving with redshift. We use these constraints to consider the future for ground-based short-submillimeter surveys.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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".