Star Formation at Very Low Metallicity. I. Chemistry and Cooling at Low Densities
Bibliographic record
Abstract
We present a simplified chemical and thermal model designed to allow computationally efficient study of the thermal evolution of metal-poor gas within large numerical simulations. Our main simplification is the neglect of the molecular chemistry of the heavy elements. The only molecular chemistry retained within the model is the formation and destruction of molecular hydrogen. Despite this major simplification, the model allows for accurate treatment of the thermal evolution of the gas within a large volume of parameter space. It is valid for temperatures 50 < T < 10,000 K and metallicities 0 < Z < 0.1 Z ☉ . In gas with a metallicity Z = 0.1 Z ☉ , and in the absence of an incident ultraviolet radiation field, it is valid for hydrogen number densities n H ≲ 500/ t char cm -3 , where t char is the size in megayears of the characteristic physical timescale of interest in the problem. If Z ≪ 0.1 Z ☉ , or if a strong ultraviolet radiation field is present, then the model remains accurate up to significantly higher densities. We also discuss some possible applications of this model.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".