Kinematics and Feedback in H ii Regions in the Dwarf Starburst Galaxy IC 10
Bibliographic record
Abstract
Abstract We present a survey of the central region of the nearest starburst galaxy, IC 10, using the W. M. Keck Observatory Keck Cosmic Web Imager (KCWI) at high spectral and spatial resolution. We map the central starburst of IC 10 to sample the kinematic and ionization properties of the individual star-forming regions. Using the low spectral resolution mode of KCWI, we map the oxygen abundance, and with the high spectral resolution mode, we identify 46 individual H II regions. These H II regions have an average radius of 4.0 pc, star formation rate ∼1.3 × 10 −4 M ⊙ yr −1 , and velocity dispersion ∼16 km s −1 . None of the H II regions appear to be virialized ( α vir ≫ 1), and on average, they show evidence of ongoing expansion. IC 10's H II regions are offset from the star-forming-region size–luminosity scaling relationships, as well as Larson’s Law that relates size and velocity dispersion. We investigate the balance of inward and outward pressure, P in and P out , finding P out > P in in 89% of H II regions, indicating feedback-driven expansion even in these low-mass H II regions. We find warm gas pressure ( P gas ) provides the dominant contribution to the outward pressure ( P out ). This counteracts the inward pressure, which is dominated by turbulence in the surrounding gas rather than self-gravity. Five H II regions show evidence of outflows that are most likely supported by either stellar winds (two regions) or champagne flows (three regions). These observations provide new insights into the state of the star-forming regions in IC 10 and negative feedback from low-mass clusters.
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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 | 0.000 |
| 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 | 0.000 | 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".