Counterparts of candidate dusty starbursts at <i>z</i> &gt; 6
Bibliographic record
Abstract
ABSTRACT We present an analysis of the optical-to-near-infrared (IR) counterparts of a sample of candidate dusty starbursts at z > 6. These objects were pre-selected based on the rising trend of their far-IR-to-sub-millimeter spectral energy distributions and the fact that they are radio-weak. Their precise positions are available through millimeter and/or radio interferometry, which enable us to search for their counterparts in the deep optical-to-near-IR images. The sample includes five z > 6 candidates. Three of them have their counterparts identified, one is still invisible in the deepest images, and one is a known galaxy at z = 5.667 that is completely blocked by a foreground galaxy. The three with counterparts identified are analysed using population synthesis model, and they have photometric redshift solutions ranging from 7.5 to 9.0. Assuming that they are indeed at these redshifts and that they are not gravitationally lensed, their total IR luminosities are $10^{13.8-14.1}\, {\rm L}_\odot$ and the inferred star formation rates are 6.3–13 $\times 10^3\, {\rm M}_\odot$ yr−1. The existence of dusty starbursts at such redshifts would imply that the Universe must be forming stars intensely very early in time in at least some galaxies, otherwise there would not be enough dust to produce the descendants observed at these redshifts. The inferred host galaxy stellar masses of these three objects, which are at $\gtrsim 10^{11}\, {\rm M}_\odot$ (if not affected by gravitational lensing), present a difficulty in explanation unless we are willing to accept that their progenitors either kept forming stars at a rate of $\gtrsim 10^3\, {\rm M}_\odot$ yr−1 or were formed through intense instantaneous bursts. Spectroscopic confirmation of such objects will be imperative.
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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 | 0.001 |
| 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 | 0.000 |
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".