WISDOM Project – XXIV. Giant molecular clouds of the spiral galaxy NGC 5064: high fraction of retrograde rotation
Bibliographic record
Abstract
ABSTRACT We present high-resolution ($0. 14\,\mathrm{ arcsec}\times 0. 12\,\mathrm{ arcsec}$ or $31\times 25$ pc$^2$) Atacama Large Millimeter/sub-millimeter Array $^{12}$CO(J = 2–1) observations of the spiral galaxy NGC 5064. Our study identifies 478 molecular clouds, of which 387 are resolved both spatially and spectrally. These clouds exhibit similarities to those of the Milky Way in terms of their sizes, molecular gas masses, velocity dispersions, velocity gradients, and Larson relations. However, the NGC 5064 clouds stand out with slightly higher gas mass surface densities, lower virial parameters ($\langle \alpha _{\rm vir}\rangle =0.48\pm 0.03$ assuming a standard conversion factor $X_{\rm CO}=2\times 10^{20}$ cm$^{-2}$ (K km s$^{-1})^{-1}$; $\alpha _{\rm vir} = 1$ for a lower conversion factor of $X_{\rm CO}=0.96\pm 0.02\times 10^{20}$ cm$^{-2}$ (K km s$^{-1})^{-1}$), and an unusually high fraction of retrograde rotation ($f_{\rm retro}\approx 67~{{\ \rm per\ cent}}$). Retrograde clouds are 18 per cent larger, 58 per cent more massive, 15 per cent more turbulent and have 17 per cent larger gas mass surface densities than prograde clouds. The velocity gradients in the clouds seem to arise from turbulence rather than cloud’s intrinsic rotation or large-scale galaxy rotation. Cloud–cloud collisions provide the most plausible explanation for the elevated retrograde fraction, though further investigation is needed to confirm this scenario. Projection effects due to the galaxy’s high inclination ($i = 70{_{.}^{\circ}} 8$) may further enhance the apparent retrograde fraction. Confirmation using less inclined systems is essential to determine whether the observed dominance of retrograde rotation reflects a genuine physical phenomenon or is significantly shaped by projection effects.
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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 | 0.001 | 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 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.022 | 0.010 |
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".