ΛCDM not dead yet: massive high-<i>z</i> Balmer break galaxies are less common than previously reported
Bibliographic record
Abstract
ABSTRACT Early JWST observations that targeted so-called double-break sources (attributed to Lyman and Balmer breaks at z > 7), reported a previously unknown population of very massive, evolved high-redshift galaxies. This surprising discovery led to a flurry of attempts to explain these objects’ unexpected existence including invoking alternatives to the standard Λ cold dark matter (ΛCDM) cosmological paradigm. To test these early results, we adopted the same double-break candidate galaxy selection criteria to search for such objects in the JWST images of the CAnadian Near Infrared Imager and Slitless Spectrograph (NIRISS) Unbiased Cluster Survey (CANUCS), and found a sample of 19 sources over five independent CANUCS fields that cover a total effective area of ∼60 arcmin2 at z ∼ 8. However, (1) our spectral energy distribution fits do not yield exceptionally high-stellar masses for our candidates, while (2) spectroscopy of five of the candidates shows that while all five are at high redshifts, their red colours are due to high-equivalent width emission lines in star-forming galaxies rather than Balmer breaks in massive, evolved systems. Additionally, (3) field-to-field variance leads to differences of ∼1.5 dex in the maximum stellar masses measured in the different fields, suggesting that the early single-field JWST observations may have suffered from cosmic variance and/or sample bias. Finally, (4) we show that the presence of even a single massive outlier can dominate conclusions from small samples such as those in early JWST observations. In conclusion, we find that the double-break sources in CANUCS are not sufficiently massive or numerous to warrant questioning the standard ΛCDM paradigm.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".