EPOCHS paper – X. Environmental effects on Galaxy formation and protocluster Galaxy candidates at 4.5 &lt; <i>z</i> &lt; 10 from JWST observations
Bibliographic record
Abstract
ABSTRACT In this paper, we describe our search for galaxy protocluster candidates at $4.5{<} z {<} 10$ and explore the environmental and physical properties of their member galaxies identified through JWST wide-field surveys within the CEERS (Cosmic Evolution Early Release Science), JADES (JWST Advanced Deep Extragalactic Survey), and PEARLS (Prime Extragalactic Areas for Reionization and Lensing Science) NEP-TDF (North Ecliptic Pole Time-Domain Fields). Combining with Hubble Space Telescope (HST) data, we identify 2948 robust $z>4.5$ galaxy candidates within an area of 185.4 arcmin$^2$. We determine nearest neighbour statistics and galaxy environments. We find that high-z galaxies in overdense environments exhibit higher star formation activity compared to those in underdense regions. Galaxies in dense environments have a slightly increased star formation rate (SFR) at a given mass compared with galaxies in the lower density environments. At the high-mass end, we also find a gradual flattening of the $M_{\star }$-SFR slope. We find that galaxies in high-density regions often have redder ultraviolet slopes than those in low-density regions, suggesting more dust extinction, weaker Ly α emission, and/or a higher damped Ly α absorption. The mass–size relation shows a weak positive correlation between galaxy size and local density. Furthermore, we quantitatively assess the probability of a galaxy belonging to a protocluster candidate. In total, we identified 26 overdensities at $z=5{\!-\!}7$ and estimate their dark matter halo masses. We find that all proto-cluster candidates could evolve into clusters with $M_{\rm halo} > 10^{14}{\rm M}_{\odot }$ at $z = 0$, thereby supporting the theoretical and simulation predictions of cluster formation. Notably, this marks an early search for protocluster candidates in JWST wide field based on photometric data, providing valuable candidates to study cosmic structure formation at the early stages.
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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 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".