The nature of 500 micron risers I: SMA observations
Bibliographic record
Abstract
ABSTRACT We present SMA observations at resolutions from 0.35 to 3 arcsec of a sample of 34 candidate high redshift dusty star forming galaxies (DSFGs). These sources were selected from the HerMES Herschel survey catalogues to have SEDs rising from 250 to 350 to 500 μm, a population termed 500-risers. We detect counterparts to 24 of these sources, with four having two counterparts. We conclude that the remaining ten sources that lack detected counterparts are likely to have three or more associated sources which blend together to produce the observed Herschel source. We examine the role of lensing, which is predicted to dominate the brightest (F500 > 60 mJy) half of our sample. We find that while lensing plays a role, at least 35 per cent of the bright sources are likely to be multiple sources rather than the result of lensing. At fainter fluxes we find a blending rate comparable to, or greater than, the predicted 40 per cent. We determine far-IR luminosities and star formation rates for the non-multiple sources in our sample and conclude that, in the absence of strong lensing, our 500-risers are very luminous systems with LFIR > 1013 L⊙ and star formation rates >1000 M⊙ yr−1.
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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 | 0.001 |
| 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) | 0.002 | 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 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".