Star formation activity of low-mass galaxies at the peak epoch of galaxy formation probed by deep narrow-band imaging
Bibliographic record
Abstract
Low-mass galaxies at high redshifts are the building blocks of more massive galaxies at later times and are thus key populations for understanding galaxy formation and evolution. We have made deep narrow-band observations for two protoclusters and the general field in COSMOS at $z$ $\sim$ 2. In a clumpy young protocluster, USS1558$-$003, at $z$ = 2.53, we find many star-forming galaxies well above the star-forming main sequence of field galaxies at the low-mass end ($M_{\star}/\mathrm{M_{\odot}}<10^{8.9}$). This suggests that some environmental effects may be at work in low-mass galaxies in high-density regions to enhance their star formation activities. In the core of this protocluster, we also find that enhanced star formation activity of middle-mass galaxies ($10^{8.9} < M_{\star}/\mathrm{M_{\odot}} < 10^{10.2}$) while such trends are not observed in a more mature protocluster, PKS1138$-$262 at $z$ = 2.16. We expect these activities to be mainly due to galaxy mergers/interactions and differences in the amount of cold gas accretion. As one piece of evidence, we show that the star formation activity within individual galaxies in the protoclusters is more centrally concentrated than those in the field. This is probably due to the enhanced interactions between galaxies in the protocluster, which can reduce the angular momentum of the gas, drive the gas towards the galaxy center, and lead to a central starburst.
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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 | 0.001 | 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".