Characterization of Two 2 mm detected Optically Obscured Dusty Star-forming Galaxies
Bibliographic record
Abstract
Abstract The 2 mm Mapping Obscuration to Reionization with ALMA (MORA) Survey was designed to detect high-redshift (z ≳ 4), massive, dusty star-forming galaxies (DSFGs). Here we present two likely high-redshift sources, identified in the survey, whose physical characteristics are consistent with a class of optical/near-infrared (OIR)-invisible DSFGs found elsewhere in the literature. We first perform a rigorous analysis of all available photometric data to fit spectral energy distributions and estimate redshifts before deriving physical properties based on our findings. Our results suggest the two galaxies, called MORA-5 and MORA-9, represent two extremes of the “OIR-dark” class of DSFGs. MORA-5 ( z phot = 4.3 − 1.3 + 1.5 ) is a significantly more active starburst with a star formation rate (SFR) of 830 − 190 + 340 M ⊙ yr−1 compared to MORA-9 ( z phot = 4.3 − 1.0 + 1.3 ), whose SFR is a modest 200 − 60 + 250 M ⊙ yr−1. Based on the stellar masses (M ⋆ ≈ 1010−11 M ⊙), space density (n ∼ (5 ± 2) × 10−6 Mpc−3, which incorporates two other spectroscopically confirmed OIR-dark DSFGs in the MORA sample at z = 4.6 and z = 5.9), and gas depletion timescales (<1 Gyr) of these sources, we find evidence supporting the theory that OIR-dark DSFGs are the progenitors of recently discovered 3 < z < 4 massive quiescent 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".