A high dust emissivity index β for a CO-faint galaxy in a filamentary Lyα nebula at <i>z</i> = 3.1
Bibliographic record
Abstract
Abstract We present CO J = 4–3 line and 3 mm dust continuum observations of a 100 kpc-scale filamentary Lyα nebula (SSA22 LAB18) at z = 3.1 using the Atacama Large Millimeter/submillimeter Array (ALMA). We detected the CO J = 4–3 line at a systemic zCO = 3.093 ± 0.001 at 11 σ from one of the ALMA continuum sources associated with the Lyα filament. We estimated the CO J = 4–3 luminosity of $L^{\prime }_{\rm {CO(4-3)}}=(2.3 \pm 0.2)\times 10^{9}\:$K km s−1 pc2 for this CO source, which is one order of magnitude smaller than those of typical z > 1 dusty star-forming galaxies (DSFGs) of similar far-infrared luminosity LIR ∼ 1012 L⊙. We derived a molecular gas mass of $M_{\rm {gas}} = (4.4^{+0.9}_{-0.6}) \times 10^{9}\, M_{{\odot }}$ and a star-formation rate of SFR =270 ± 160 M⊙ yr−1. We also estimated a gas depletion time of τdep = 17 ± 10 Myr, which is shorter than those of typical DSFGs. It is suggested that this source is in the transition phase from DSFG to a gas-poor, early-type galaxy. From ALMA to Herschel multi-band dust continuum observations, we measured a dust emissivity index β = 2.3 ± 0.2, which is similar to those of local gas-poor, early-type galaxies. From recent laboratory experiments, the specific chemical compositions needed to reproduce such a high β for interstellar dust at the submillimeter wavelengths. ALMA CO and multi-band dust continuum observations can constrain the evolutionary stage of high-redshift galaxies through τdep and β, and thus we can investigate the chemical composition of dust even in the early Universe.
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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 | 0.001 | 0.000 |
| 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) | 0.001 | 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".