The slowly evolving role of environment in a spectroscopic survey of star formation in M* > 5 × 108 M⊙ galaxies since z ∼ 1
Bibliographic record
Abstract
We present a deep [O ii] emission-line survey of faint galaxies (22.5< KAB <24) in the Chandra Deep Field South (CDFS) and the Faint Infra-Red Extragalactic Survey (FIRES) field. With these data we measure the star formation rate (SFR) in galaxies in the stellar mass range 8.85 ≲ log (M*/M⊙) ≲ 9.5 at 0.62 < z < 0.885, to a limit of SFR ∼ 0.1 M⊙ yr−1. The presence of a massive cluster (MS1054−03) in the FIRES field, and of significant large-scale structure in the CDFS field, allows us to study the environmental dependence of SFRs amongst this population of low-mass galaxies. Comparing our results with more massive galaxies at this epoch, with our previous survey [Redshift One LDSS-3 Emission Line Survey (ROLES)] at the higher redshift z ∼ 1, and with Sloan Digital Sky Survey (SDSS) Stripe 82 data, we find no significant evolution of the stellar mass function of star-forming galaxies between z = 0 and z ∼ 1, and no evidence that its shape depends on environment. The correlation between specific star formation rate (sSFR) and stellar mass at z ∼ 0.75 has a power-law slope of β ∼ −0.2, with evidence for a steeper relation at the lowest masses. The normalization of this correlation lies as expected between that corresponding to z ∼ 1 and the present day. The global SFR density is consistent with an evolution of the form (1 + z)2 over 0 < z < 1, with no evidence for a dependence on stellar mass. The sSFR of these star-forming galaxies at z ∼ 0.75 does not depend upon the density of their local environment. Considering just high-density environments, the low-mass end of the sSFR–M* relation in our data is steeper than that in Stripe 82 at z = 0, and shallower than that measured by ROLES at z = 1. Evolution of low-mass galaxies in dense environments appears to be more rapid than in the general 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 | 0.001 |
| 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) | 0.001 | 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".