The star formation reference survey – IV. Stellar mass distribution of local star-forming galaxies
Bibliographic record
Abstract
ABSTRACT We constrain the mass distribution in nearby, star-forming galaxies with the Star Formation Reference Survey (SFRS), a galaxy sample constructed to be representative of all known combinations of star formation rate, dust temperature, and specific star formation rate (sSFR) that exist in the Local Universe. An innovative 2D bulge/disc decomposition of the 2MASS/Ks-band images of the SFRS galaxies yields global luminosity and stellar mass functions (MFs), along with separate MFs for their bulges and discs. These accurate MFs cover the full range from dwarf galaxies to large spirals, and are representative of star-forming galaxies selected based on their infrared luminosity, unbiased by active galactic nucleus content and environment. We measure an integrated luminosity density j = 1.72 ± 0.93 × 109 L$_{\odot }\, h^{-1}$ Mpc−3 and a total stellar mass density ρM = 4.61 ± 2.40 × 108 M$_{\odot }\, h^{-1}$ Mpc−3. While the stellar mass of the average star-forming galaxy is equally distributed between its sub-components, discs globally dominate the mass density budget by a ratio 4:1 with respect to bulges. In particular, our functions suggest that recent star formation happened primarily in massive systems, where they have yielded a disc stellar mass density larger than that of bulges by more than 1 dex. Our results constitute a reference benchmark for models addressing the assembly of stellar mass on the bulges and discs of local (z = 0) star-forming galaxies.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| 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) | 0.002 | 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".