Giant molecular clouds and their type classification in M 74: Toward understanding star formation and cloud evolution
Bibliographic record
Abstract
Abstract We investigated the giant molecular clouds (GMCs) in M 74 (NGC 628), using data obtained from the PHANGS (Physics at High Angular resolution in Nearby GalaxieS) project. We applied GMC types according to the activity of star formation: Type I without star formation, Type II with H$\alpha$ luminosity ($L_{\mathrm{H\alpha }}$) less than $10^{37.5}\ \rm{erg\ s ^{-1}}$, and Type III with $L_{\mathrm{H\alpha }}$ greater than $10^{37.5}\ \rm{erg\ s^{-1}}$. A total of 432 GMCs were identified, with 59, 201, and 172 GMCs, for Types I, II, and III, respectively. The size and mass of the GMCs range from 23 to 238 pc and $10^{4.9}$ to $10^{7.1}\, M_{\odot }$, indicating that the mass and radius increase from Types I to III. Clusters younger than 4 Myr and H ii regions are concentrated within 150 pc of a GMC, indicating a tight association between these young objects and GMCs. The virial ratio decreases from Type I to Type III, indicating that Type III GMCs are the most gravitationally relaxed among the three. We interpret that the GMCs evolve from Type I to Type III, as previously observed in the Large Magellanic Cloud. Based on a steady-state assumption, the estimated evolutionary timescales of Types I, II, and III are 1, 5, and 4 Myr, respectively. We assume that the timescale of Type III is equal to the age of the associated clusters, indicating a GMC lifetime of 10 Myr or longer. Although Chevance et al. (2020, MNRAS, 493, 2872) investigated GMCs using the same PHANGS dataset of M 74, they did not define a GMC, reaching an evolutionary picture with a 20 Myr duration of the non-star-forming phase, which is five times longer than 4 Myr. We compare the present results with those of Chevance et al. (2020, MNRAS, 493, 2872) and argue that defining individual GMCs is essential for understanding GMC evolution.
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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 | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".