Consequences of cosmic microwave background-regulated star formation
Bibliographic record
Abstract
It has been hypothesized that the cosmic microwave background (CMB) provides a temperature floor for collapsing protostars that can regulate the process of star formation and result in a top-heavy initial mass function at high metallicity and high redshift. We examine whether this hypothesis has any testable observational consequences. First we determine, using a set of hydrodynamic galaxy formation simulations, that the CMB temperature floor would have influenced the majority of stars formed at redshifts between z=3 and 6, and probably even to higher redshift. Five signatures of CMB-regulated star formation are: (1) a higher supernova rate than currently predicted at high redshift; (2) a systematic discrepancy between direct and indirect measurements of the high redshift star formation rate; (3) a lack of surviving globular clusters that formed at high metallicity and high redshift; (4) a more rapid rise in the metallicity of cosmic gas than is predicted by current simulations; and (5) an enhancement in the abundances of alpha elements such as O and Mg at metallicities -2 < [Fe/H] < -0.5. Observations are not presently able to either confirm or rule out the presence of these signatures. However, if correct, the top-heavy IMF of high-redshift high-metallicity globular clusters could provide an explanation for the observed bimodality of their metallicity distribution.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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".