The SCUBA Half Degree Extragalactic Survey (SHADES) – IX. The environment, mass and redshift dependence of star formation
Bibliographic record
Abstract
We present a comparison between the SCUBA (Submillimetre Common User Bolometer Array) Half Degree Extragalactic Survey (SHADES) at 450 and 850 μm in the Lockman Hole East with a deep Spitzer Space Telescope survey at 3.6–24 μm conducted in guaranteed time. Using stacking analyses we demonstrate a striking correspondence between the galaxies contributing the submm extragalactic background light, with those likely to dominate the backgrounds at Spitzer wavelengths. Using a combination BRIzK plus Spitzer photometric redshifts, we show that at least a third of the Spitzer-identified submm galaxies at 1 < z < 1.5 appear to reside in overdensities when the density field is smoothed at 0.5–2 Mpc comoving diameters, supporting the high-redshift reversal of the local star formation–galaxy density relation. We derive the dust-shrouded cosmic star formation history of galaxies as a function of assembled stellar masses. For model stellar masses <1011M⊙, this peaks at lower redshifts than the ostensible z∼ 2.2 maximum for submm point sources, adding to the growing consensus for ‘downsizing’ in star formation. Our surveys are also consistent with ‘downsizing’ in mass assembly. Both the mean star formation rates 〈dM*/dt〉 and specific star formation rates 〈(1/M*) d M*/d t〉 are in striking disagreement with some semi-analytic predictions from the Millenium Simulation. The discrepancy could either be resolved with a top-heavy initial mass function, or a significant component of the submm flux heated by the interstellar radiation field.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".