CANUCS/Technicolor: JWST Medium-band Photometry Finds Half of the Star Formation at <i>z</i> > 7.5 Is Obscured
Bibliographic record
Abstract
Abstract We present a sample of 110 high-redshift (z > 7.5) galaxies from the CANUCS and Technicolor surveys, showcasing photometry in every wide- and medium-band NIRCam filter in addition to ancillary Hubble Space Telescope data sampling 0.4–5 μm (22 JWST bands out of 29 bands total). Additionally, 47 (43%) galaxies in our sample meet criteria to be classified as extreme emission line galaxies, 17 (15%) of which are completely missed by typical dropout selections due to faint ultraviolet (UV) emission. By fitting the spectral energy distributions covering the rest-frame UV to optical at z > 7.5, we investigate the dust obscuration properties, giving an unbiased view of dust buildup in high-redshift galaxies free from spectroscopic follow-up selection effects. Dust attenuation correlates with stellar mass, but more strongly with star formation rate. We find typical galaxies at z > 7.5 have ∼25% of their star formation obscured. However, since galaxies with higher star formation rates suffer more attenuation, ∼50% of the total star formation rate density at 7.5 < z < 9 is obscured. The obscured fraction drops to ∼25% in our 9 < z < 12 bin, possibly due to substantial dust grain growth in the interstellar medium not having time to occur. Extrapolating the decline in dust obscuration of galaxies to higher redshifts, we infer that dust obscuration should approach zero at z > 15, implying that epoch as when dust first forms in bright 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 | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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".