The Photometric and Kinematic Structure of Face‐on Disk Galaxies. I. Sample Definition, Hα Integral Field Spectroscopy, and H <scp>i</scp> Line Widths
Bibliographic record
Abstract
We present a survey of the photometric and kinematic properties of 39 nearby, nearly face-on disk galaxies. Our approach exploits echelle-resolution integral-field spectroscopy of the Hα regions, obtained with DensePak on the WIYN 3.5 m telescope Bench Spectrograph. These data are complemented by H I line profiles observed with the Nançay radio telescope for 25 of these sample galaxies. Twelve additional line widths are available for sample galaxies from the literature. In this paper, we introduce the goals of this survey, define the sample selection algorithm, and amass the integral field spectroscopic data and H I line widths. We establish spatially integrated Hα line widths for the sample. We test the veracity of these spatially integrated line profiles by convolving narrowband imaging data with velocity field information for one of the sample galaxies, PGC 38268, and also by comparing to H I line profiles. We find H I and Hα line profiles to be similar in width but different in shape, indicating that we are observing different spatial distributions of ionized and neutral gas in largely axisymmetric systems with flat outer rotation curves. We also find vertical velocity dispersions of the ionized disk gas within several disk scale lengths have a median value of 18 km s -1 and an 80% range of 12-26 km s -1 . This is only a factor of ~2 larger than what is observed for neutral atomic and molecular gas. With standard assumptions for intrinsic and thermal broadening for Hα, this translates into a factor of 3 range in turbulent velocities, between 8 and 25 km s -1 .
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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 | 0.002 |
| 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) | 0.004 | 0.001 |
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".