A search for the submillimetre counterparts to Lyman break galaxies
Bibliographic record
Abstract
We have carried out targeted submillimetre observations as part of a programme to explore the connection between the rest-frame ultraviolet and far-infrared properties of star-forming galaxies at high redshift, which is currently poorly understood. On the one hand, the Lyman break technique is very effective at selecting galaxies. On the other, ‘blank-field’ imaging in the submillimetre seems to turn up sources routinely, amongst which some are star-forming galaxies at similar redshifts. Already much work has been done searching for optical identifications of objects detected using the SCUBA instrument. Here we have taken the opposite approach, performing submillimetre photometry for a sample of Lyman break galaxies, the ultraviolet properties of which imply high star formation rates. The total signal from our Lyman break sample is undetected in the submillimetre, at an rms level of ∼0.5 mJy, which implies that the population of Lyman break galaxies does not constitute a large part of the recently detected blank-field submillimetre sources. However, our one detection suggests that with reasonable SCUBA integrations we might expect to detect those few Lyman break galaxies that are far-infrared brightest.
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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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".