STAR FORMATION IN THE OUTER DISK OF SPIRAL GALAXIES
Bibliographic record
Abstract
We combine new deep and wide field of view Hα imaging of a sample of eight nearby ( d ≈ 17 Mpc) spiral galaxies with new and archival H i and CO imaging to study the star formation and the star formation regulation in the outer disk. We find that, in agreement with previous studies, star formation in the outer disk has low covering fractions, and star formation is typically organized into spiral arms. The star formation in the outer disk is at extremely low levels, with typical star formation rate surface densities of ∼10 −5 to 10 −6 M ☉ yr −1 kpc −2 . We find that the ratio of the radial extent of detected H ii regions to the radius of the H i disk is typically ≳85%. This implies that in order to further our understanding of the implications of extended star formation, we must further our understanding of the formation of extended H i disks. We measure the gravitational stability of the gas disk, and find that the outer gaseous disk is typically a factor of ∼2 times more stable than the inner star-forming disk. We measure the surface density of outer disk H i arms, and find that the disk is closer to gravitational instability along these arms. Therefore, it seems that spiral arms are a necessary, but not sufficient, requirement for star formation in the outer disk. We use an estimation of the flaring of the outer gas disk to illustrate the effect of flaring on the Schmidt power-law index; we find that including flaring increases the agreement between the power-law indices of the inner and outer disks.
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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) | 0.000 | 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) | 0.000 | 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".