On the nature of the first galaxies selected at 350 µm
Bibliographic record
Abstract
[abridged] We present constraints on the nature of the first galaxies selected at 350 microns. The sample includes galaxies discovered in the deepest blank-field survey at 350 microns (in the Bootes Deep Field) and also later serendipitous detections in the Lockman Hole. Spectral energy distribution templates are fit to identified counterparts, and the sample is found to comprise IR-luminous galaxies at 1<z<3 predominantly powered by star formation. The first spectrum of a 350-micron-selected galaxy provides an additional confirmation, showing prominent dust grain features typically associated with star-forming galaxies. Compared to submillimeter galaxies selected at 850 and 1100 microns, galaxies selected at 350 microns have a similar range of far-infrared color temperatures. However, no 350-micron-selected sources are reliably detected at 850 or 1100 microns. Galaxies in our sample with redshifts 1<z<2 show a tight correlation between the far- and mid-infrared flux densities, but galaxies at higher redshifts show a large dispersion in their mid- to far-infrared colors. The 350-micron flux densities (15<S(350)<40 mJy) place these objects near the Herschel/SPIRE 350-micron confusion threshold, with the lower limit on the star formation rate density suggesting the bulk of the 350-micron contribution will come from less luminous infrared sources and normal galaxies.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".