GALAXY STELLAR MASS ASSEMBLY BETWEEN 0.2 <<i>z</i>< 2 FROM THE S-COSMOS SURVEY
Bibliographic record
Abstract
We follow the galaxy stellar mass assembly by morphological and spectral type in the COSMOS 2 deg 2 field. We derive the stellar mass functions and stellar mass densities from z = 2 to z = 0.2 using 196,000 galaxies selected at F 3.6 μm > 1 μJy with accurate photometric redshifts ( at i + < 22.5). Using a spectral classification, we find that z ∼ 1 is an epoch of transition in the stellar mass assembly of quiescent galaxies. Their stellar mass density increases by 1.1 dex between z = 1.5–2 and z = 0.8–1 (Δ t ∼ 2.5 Gyr), but only by 0.3 dex between z = 0.8–1 and z ∼ 0.1 (Δ t ∼ 6 Gyr). Then, we add the morphological information and find that 80%–90% of the massive quiescent galaxies have an elliptical morphology at z < 0.8. Therefore, a dominant mechanism links the shutdown of star formation and the acquisition of an elliptical morphology in massive galaxies. Still, a significant fraction of quiescent galaxies present a Spi/Irr morphology at low mass (40%–60% at ), but this fraction is smaller than predicted by semi-analytical models using a "halo quenching" recipe. We also analyze the evolution of star-forming galaxies and split them into "intermediate activity" and "high activity" galaxies. We find that the most massive "high activity" galaxies end their high star formation rate phase first. Finally, the space density of massive star-forming galaxies becomes lower than the space density of massive elliptical galaxies at z < 1. As a consequence, the rate of "wet mergers" involved in the formation of the most massive ellipticals must decline very rapidly at z < 1, which could explain the observed slow down in the assembly of these quiescent and massive sources.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| 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) | 0.003 | 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".