The evolution of submillimetre galaxies: two populations and a redshift cut-off
Bibliographic record
Abstract
We explore the epoch dependence of number density and star formation rate for submillimetre galaxies (SMGs) found at 850 μm. The study uses a sample of 38 SMG in the Great Observatories Origins Deep Survey (GOODS)-N field, for which cross-waveband identifications have been obtained for 35/38 members together with redshift measurements or estimates. A maximum-likelihood analysis is employed, along with the ‘single-source-survey’ technique. We find a diminution in both space-density and star formation rate at z > 3, closely mimicking the redshift cut-offs found for quasi-stellar objects (QSOs) selected in different wavebands. The diminution in redshift is particularly marked at a significance level too small to measure. The data further suggest, at a significance level of about 0.001, that two separately evolving populations may be present, with distinct luminosity functions. These results parallel the different evolutionary behaviours of Luminous Infrared Galaxies and Ultra-Luminous Infrared Galaxies, and represent another manifestation of ‘cosmic down-sizing’, suggesting that differential evolution extends to the most extreme star-forming 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 | 0.003 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".