The GOGREEN survey: the environmental dependence of the star-forming galaxy main sequence at 1.0 &lt; <i>z</i> &lt; 1.5
Bibliographic record
Abstract
ABSTRACT We present results on the environmental dependence of the star-forming galaxy main sequence in 11 galaxy cluster fields at 1.0 < z < 1.5 from the Gemini Observations of Galaxies in Rich Early Environments Survey (GOGREEN) survey. We use a homogeneously selected sample of field and cluster galaxies whose membership is derived from dynamical analysis. Using [$\rm{O{\small II}}$]-derived star formation rates (SFRs), we find that cluster galaxies have suppressed SFRs at fixed stellar mass in comparison to their field counterparts by a factor of 1.4 ± 0.1 (∼3.3σ) across the stellar mass range: 9.0 < log (M*/M⊙) < 11.2. We also find that this modest suppression in the cluster galaxy star-forming main sequence is mass and redshift dependent: the difference between cluster and field increases towards lower stellar masses and lower redshift. When comparing the distribution of cluster and field galaxy SFRs to the star-forming main sequence, we find an overall shift towards lower SFRs in the cluster population, and note the absence of a tail of high SFR galaxies as seen in the field. Given this observed suppression in the cluster galaxy star-forming main sequence, we explore the implications for several scenarios such as formation time differences between cluster and field galaxies, and environmentally induced star formation quenching and associated time-scales.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".