IONIZED GAS TOWARD MOLECULAR CLUMPS: PHYSICAL PROPERTIES OF MASSIVE STAR-FORMING REGIONS
Bibliographic record
Abstract
We have conducted a search for ionized gas at 3.6 cm, using the Very Large Array, toward 31 Galactic intermediate- and high-mass clumps detected in previous millimeter continuum observations. In the 10 observed fields, 35 H ii regions are identified, of which 20 are newly discovered. Many of the H ii regions are multiply peaked indicating the presence of a cluster of massive stars. We find that the ionized gas tends to be associated toward the millimeter clumps; of the 31 millimeter clumps observed, nine of these appear to be physically related to ionized gas, and a further six have ionized gas emission within 1'. For clumps with associated ionized gas, the combined mass of the ionizing massive stars is compared to the clump masses to provide an estimate of the instantaneous star formation efficiency. These values range from a few percent to 25%, and have an average of 7% ± 8%. We also find a correlation between the clump mass and the mass of the ionizing massive stars within it, which is consistent with a power law. This result is comparable to the prediction of star formation by competitive accretion that a power-law relationship exists between the mass of the most massive star in a cluster and the total mass of the remaining stars.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".