ON THE NATURE OF THE FIRST GALAXIES SELECTED AT 350 μm
Bibliographic record
Abstract
We present constraints on the nature of the first galaxies selected at 350 μm. The sample includes galaxies discovered in the deepest blank-field survey at 350 μm (in the Boötes Deep Field) and also later serendipitous detections in the Lockman Hole. In determining multiwavelength identifications, the 350 μm position and map resolution of the second generation Submillimeter High Angular Resolution Camera are critical, especially in the cases where multiple radio sources exist and the 24 μm counterparts are unresolved. Spectral energy distribution templates are fitted 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 μm 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 μm, galaxies selected at 350 μm have a similar range of far-infrared color temperatures. However, no 350 μm selected sources are reliably detected at 850 or 1100 μm. 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. This implies a limit to which the mid-IR emission traces the far-IR emission in star-forming galaxies. The 350 μm flux densities (15 < S 350 < 40 mJy) place these objects near the Herschel /SPIRE 350 μm confusion threshold, with the lower limit on the star formation rate density suggesting the bulk of the 350 μm contribution will come from less luminous infrared sources and normal galaxies. Therefore, the nature of the dominant source of the 350 μm background—star-forming galaxies in the epoch of peak star formation in the universe—could be more effectively probed using ground-based instruments with their angular resolution and sensitivity offering significant advantages over space-based imaging.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".