The EDGE-CALIFA Survey: Spatially Resolved <sup>13</sup>CO(1–0) Observations and Variations in <sup>12</sup>CO(1–0)/<sup>13</sup>CO(1–0) in Nearby Galaxies on Kiloparsec Scales
Bibliographic record
Abstract
Abstract We present 13CO(J = 1 → 0) observations for the EDGE-CALIFA survey, which is a mapping survey of 126 nearby galaxies at a typical spatial resolution of 1.5 kpc. Using detected 12CO emission as a prior, we detect 13CO in 41 galaxies via integrated line flux over the entire galaxy and in 30 galaxies via integrated line intensity in resolved synthesized beams. Incorporating our CO observations and optical IFU spectroscopy, we perform a systematic comparison between the line ratio 12 / 13 ≡ I [ 12 CO ( J = 1 → 0 ) ] / I [ 13 CO ( J = 1 → 0 ) ] and the properties of the stars and ionized gas. Higher 12 / 13 values are found in interacting galaxies compared to those in noninteracting galaxies. The global 12 / 13 slightly increases with infrared color F 60/F 100 but appears insensitive to other host-galaxy properties such as morphology, stellar mass, or galaxy size. We also present azimuthally averaged 12 / 13 profiles for our sample up to a galactocentric radius of 0.4r 25 (∼6 kpc), taking into account the 13CO nondetections by spectral stacking. The radial profiles of 12 / 13 are quite flat across our sample. Within galactocentric distances of 0.2r 25, the azimuthally averaged 12 / 13 increases with the star formation rate. However, Spearman rank correlation tests show the azimuthally averaged 12 / 13 do
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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 | 0.000 |
| 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) | 0.002 | 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".