<i>Herschel</i>observations of a<i>z</i>∼ 2 stellar mass selected galaxy sample drawn from the GOODS NICMOS Survey
Bibliographic record
Abstract
We present a study of the far-infrared (IR) properties of a stellar mass selected sample of 1.5 < z < 3 galaxies with log (M*/M⊙) > 9.5 drawn from the Great Observatories Origins Deep Survey (GOODS) Near Infrared Camera and Multi-Object Spectrometer (NICMOS) Survey (GNS), the deepest H-band Hubble Space Telescope survey of its type prior to the installation of Wide Field Camera 3 (WFC3). We use far-IR and submm data from the Photoconductor Array Camera and Spectrometer (PACS) and Spectral and Photometric Imaging Receiver (SPIRE) instruments on-board Herschel, taken from the PACS Evolutionary Probe (PEP) and Herschel Multi-Tiered Extragalactic Survey (HerMES) key projects, respectively. We find a total of 22 GNS galaxies, with median log (M*/M⊙) = 10.8 and z = 2.0, associated with 250 μm sources detected with signal-to-noise ratio (SNR) > 3. We derive mean total IR luminosity log LIR(L⊙) = 12.36 ± 0.05 and corresponding star formation rate (SFR)IR + UV = (280 ± 40) M⊙ yr−1 for these objects, and find them to have mean dust temperature Tdust ≈ 35 K. We find that the SFR derived from the far-IR photometry combined with ultraviolet (UV)-based estimates of unobscured SFR for these galaxies is on average more than a factor of 2 higher than the SFR derived from extinction-corrected UV emission alone, although we note that the IR-based estimate is subject to substantial Malmquist bias. To mitigate the effect of this bias and extend our study to fainter fluxes, we perform a stacking analysis to measure the mean SFR in bins of stellar mass. We obtain detections at the 2–4σ level at SPIRE wavelengths for samples with log (M*/M⊙) > 10. In contrast to the Herschel detected GNS galaxies, we find that estimates of SFRIR + UV for the stacked samples are comparable to those derived from extinction-corrected UV emission, although the uncertainties are large. We find evidence for an increasing fraction of dust obscured star formation with stellar mass, finding , which is likely a consequence of the mass–metallicity relation.
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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 | 0.000 |
| 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) | 0.002 | 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".