Variations in the Galactic star formation rate and density thresholds for star formation
Bibliographic record
Abstract
The conversion of gas into stars is a fundamental process in astrophysics and cosmology. Stars are known to form from the gravitational collapse of dense clumps in interstellar molecular clouds, and it has been proposed that the resulting star formation rate is proportional to either the amount of mass above a threshold gas surface density, or the gas volume density. These star formation prescriptions appear to hold in nearby molecular clouds in our Milky Way Galaxy's disc as well as in distant galaxies where the star formation rates are often much larger. The inner 500 pc of our Galaxy, the Central Molecular Zone (CMZ), contains the largest concentration of dense, high-surface density molecular gas in the Milky Way, providing an environment where the validity of star formation prescriptions can be tested. Here, we show that by several measures, the current star formation rate in the CMZ is an order-of-magnitude lower than the rates predicted by the currently accepted prescriptions. In particular, the region 1° < l < 3°.5, |b| < 0°.5 contains ∼107 M⊙ of dense (> several 103 cm−3) molecular gas – enough to form 1000 Orion-like clusters – but the present-day star formation rate within this gas is only equivalent to that in Orion. In addition to density, another property of molecular clouds must be included in the star formation prescription to predict the star formation rate in a given mass of molecular gas. We discuss which physical mechanisms might be responsible for suppressing star formation in the CMZ.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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".