A sensitive, high-resolution, wide-field IRAM NOEMA CO(1–0) survey of the very nearby spiral galaxy IC 342
Bibliographic record
Abstract
We present a new wide-field 10.75 × 10.75 arcmin 2 (≈11 × 11 kpc 2 ), high-resolution ( θ = 3.6″ ≈ 60 pc) NOEMA CO(1–0) survey of the very nearby ( d = 3.45 Mpc) spiral galaxy IC 342. The survey spans out to about 1.5 effective radii and covers most of the region where molecular gas dominates the cold interstellar medium. We resolved the CO emission into > 600 individual giant molecular clouds and associations. We assessed their properties and found that overall the clouds show approximate virial balance, with typical virial parameters of α vir = 1 − 2. The typical surface density and line width of molecular gas increase from the inter-arm region to the arm and bar region, and they reach their highest values in the inner kiloparsec of the galaxy (median Σ mol ≈ 80, 140, 160, and 1100 M ⊙ pc −2 , σ CO ≈ 6.6, 7.6, 9.7, and 18.4 km s −1 for inter-arm, arm, bar, and center clouds, respectively). Clouds in the central part of the galaxy show an enhanced line width relative to their surface densities and evidence of additional sources of dynamical broadening. All of these results agree well with studies of clouds in more distant galaxies at a similar physical resolution. Leveraging our measurements to estimate the density and gravitational free-fall time at 90 pc resolution, averaged on 1.5 kpc hexagonal apertures, we estimate a typical star formation efficiency per free-fall time of 0.45% with a 16 − 84% variation of 0.33 − 0.71% among such 1.5 kpc regions. We speculate that bar-driven gas inflow could explain the large gas concentration in the central kiloparsec and the buildup of the massive nuclear star cluster. This wide-area CO map of the closest face-on massive spiral galaxy demonstrates the current mapping power of NOEMA and has many potential applications. The data and products are publicly available.
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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 | 0.002 | 0.001 |
| 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 | 0.001 |
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".