Measuring star formation in high-z massive galaxies: a mid-infrared to submillimetre study of the GOODS NICMOS Survey sample
Bibliographic record
Abstract
We present measurements of the mean mid-infrared to submillimetre flux densities of massive (M★≳ 1011 M⊙) galaxies at redshifts 1.7 < z < 2.9, obtained by stacking positions of known objects taken from the GOODS NICMOS Survey (GNS) catalogue on maps at 24 m (Spitzer/MIPS); 70, 100 and 160 m (Herschel/PACS); 250, 350 and 500 m (BLAST); and 870 m (LABOCA). A modified blackbody spectrum fit to the stacked flux densities indicates a median [interquartile] star formation rate (SFR) of SFR = 63[48, 81] M⊙ yr−1. We note that not properly accounting for correlations between bands when fitting stacked data can significantly bias the result. The galaxies are divided into two groups, disc-like and spheroid-like, according to their Sérsic indices, n. We find evidence that most of the star formation is occurring in n≤ 2 (disc-like) galaxies, with median [interquartile] SFR = 122[100, 150] M⊙ yr−1, while there are indications that the n > 2 (spheroid-like) population may be forming stars at a median [interquartile] SFR = 14[9, 20] M⊙ yr−1, if at all. Finally, we show that star formation is a plausible mechanism for size evolution in this population as a whole, but find only marginal evidence that it is what drives the expansion of the spheroid-like galaxies.
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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 | 0.002 | 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) | 0.001 | 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".