Hyper Suprime-Cam Subaru Strategic Program: A Mass-dependent Slope of the Galaxy Size−Mass Relation at z < 1
Bibliographic record
Abstract
Abstract We present the galaxy size−mass (R e –M *) distributions using a stellar mass complete sample of ∼1.5 million galaxies, covering ∼100 deg2, with log ( M * / M ⊙ ) > 10.2 ( 9.2 ) over the redshift range 0.2 < z < 1.0 (z < 0.6) from the second public data release of the Hyper Suprime-Cam Subaru Strategic Program. We confirm that, at fixed redshift and stellar mass over the range of log ( M * / M ⊙ ) < 11 , star-forming galaxies are on average larger than quiescent galaxies. The large sample of galaxies with accurate size measurements, thanks to the excellent imaging quality, also enables us to demonstrate that the R e –M * relations of both populations have a form of a broken power law, with a clear change of slopes at a pivot stellar mass M p . For quiescent galaxies, below an (evolving) pivot mass of log ( M p / M ⊙ ) = 10.2 – 10.6 , the relation follows R e ∝ M ∗ 0.1 ; above M p the relation is steeper and follows R e ∝ M * 0.6 – 0.7 . For star-forming galaxies, below log ( M p / M ⊙ ) ∼ 10.7
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 0.005 |
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".