The H α star formation main sequence in cluster and field galaxies at <i>z</i> ∼ 1.6
Bibliographic record
Abstract
ABSTRACT We calculate H α-based star formation rates and determine the star formation rate–stellar mass relation for members of three Spitzer Adaptation of the Red-Sequence Cluster Survey (SpARCS) clusters at z ∼ 1.6 and serendipitously identified field galaxies at similar redshifts to the clusters. We find similar star formation rates in cluster and field galaxies throughout our range of stellar masses. The results are comparable to those seen in other clusters at similar redshifts, and consistent with our previous photometric evidence for little quenching activity in clusters. One possible explanation for our results is that galaxies in our z ∼ 1.6 clusters have been accreted too recently to show signs of environmental quenching. It is also possible that the clusters are not yet dynamically mature enough to produce important environmental quenching effects shown to be important at low redshift, such as ram-pressure stripping or harassment.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".