Deep near-infrared spectroscopy of submillimetre-selected galaxies
Bibliographic record
Abstract
We present the results of deep near-infrared spectroscopy of seven submillimetre-selected galaxies from the Submillimetre Common User Bolometer Array (SCUBA) 8-mJy Survey and Canada–UK Deep Submillimetre Survey (CUDSS). These galaxies were selected because they are too faint to be accessible to optical spectrographs on large telescopes. We obtain a spectroscopic redshift for one object, and likely redshifts for two more, based on a combination of marginal emission-line detections and the shape of the continuum. All three redshifts broadly agree with estimates from their radio/submm spectral energy distributions. From the emission-line strengths of these objects, we infer star formation rates of 10–25 M⊙ yr−1, while the lack of detections in the other objects imply even lower rates. By comparing our results with those of other authors, we conclude it is likely that the vast majority (more than 90 per cent) of the star formation in these objects is completely extinguished at rest-frame optical wavelengths, and the emission lines originate in a relatively unobscured region. Finally, we look at future prospects for making spectroscopic redshift determinations of submm 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 | 0.001 | 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".