Star formation scales and efficiency in Galactic spiral arms
Bibliographic record
Abstract
We positionally match a sample of infrared-selected young stellar objects, identified by combining the Spitzer Galactic Legacy Infrared Mid-Plane Survey Extraordinaire, Wide-field Infrared Survey Explorer and Herschel Space Observatory Herschel infrared Galactic Plane Survey, to the dense clumps identified in the millimetre continuum by the Bolocam Galactic Plane Survey in two Galactic lines of sight centred towards l = 30° and 40°. We calculate the ratio of infrared luminosity, LIR, to the mass of the clump, Mclump, in a variety of Galactic environments and find it to be somewhat enhanced in spiral arms compared to the interarm regions when averaged over kiloparsec scales. We find no compelling evidence that these changes are due to the mechanical influence of the spiral arm on the star formation efficiency rather than, e.g. different gradients in the star formation rate due to patchy or intermittent star formation, or local variations that are not averaged out due to small source samples. The largest variation in LIR/Mclump is found in individual clump values, which follow a lognormal distribution and have a range of over three orders of magnitude. This spread is intrinsic as no dependence of LIR/Mclump with Mclump was found. No difference was found in the luminosity distribution of sources in the arm and interarm samples and a strong linear correlation was found between LIR and Mclump.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".