WISDOM project XX. – Strong shear tearing molecular clouds apart in NGC 524
Bibliographic record
Abstract
ABSTRACT Early-type galaxies (ETGs) are known to harbour dense spheroids of stars but scarce star formation (SF). Approximately a quarter of these galaxies have rich molecular gas reservoirs yet do not form stars efficiently. We study here the ETG NGC 524, with strong shear suspected to result in a smooth molecular gas disc and low star-formation efficiency (SFE). We present new spatially resolved observations of the 12CO(2-1)-emitting cold molecular gas from the Atacama Large Millimeter/sub-millimeter Array (ALMA) and of the warm ionized-gas emission lines from SITELLE at the Canada–France–Hawaii Telescope. Although constrained by the resolution of the ALMA observations (≈37 pc), we identify only 52 GMCs with radii ranging from 30 to 140 pc, a low mean molecular gas mass surface density 〈Σgas〉 ≈ 125 M⊙ pc−2 and a high mean virial parameter 〈αobs, vir〉 ≈ 5.3. We measure spatially resolved molecular gas depletion times (τdep ≡ 1/SFE) with a spatial resolution of ≈100 pc within a galactocentric distance of 1.5 kpc. The global depletion time is ≈2.0 Gyr but τdep increases towards the galaxy centre, with a maximum τdep, max ≈ 5.2 Gyr. However, no pure H ii region is identified in NGC 524 using ionized-gas emission-line ratio diagnostics, so the τdep inferred are in fact lower limits. Measuring the GMC properties and dynamical states, we conclude that shear is the dominant mechanism shaping the molecular gas properties and regulating SF in NGC 524. This is supported by analogous analyses of the GMCs in a simulated ETG similar to NGC 524.
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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 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.022 | 0.005 |
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".