The MALATANG Survey: The L<sub>GAS</sub>–L<sub>IR</sub>Correlation on Sub-kiloparsec Scale in Six Nearby Star-forming Galaxies as Traced by HCN J = 4 → 3 and HCO<sup>+</sup>J = 4 → 3
Bibliographic record
Abstract
Abstract We present and maps of six nearby star-forming galaxies, NGC 253, NGC 1068, IC 342, M82, M83, and NGC 6946, obtained with the James Clerk Maxwell Telescope as part of the MALATANG survey. All galaxies were mapped in the central 2′ × 2′ region at 14″ (FWHM) resolution (corresponding to linear scales of ∼0.2–1.0 kpc). TheLIR–L′denserelation, where the dense gas is traced by the and the emission, measured in our sample of spatially resolved galaxies is found to follow the linear correlation established globally in galaxies within the scatter. We find that the luminosity ratio,LIR/L′dense, shows systematic variations withLIRwithin individual spatially resolved galaxies, whereas the galaxy-integrated ratios vary little. A rising trend is also found betweenLIR/L′denseratio and the warm-dust temperature gauged by the 70μm/100μm flux ratio. We find that the luminosity ratios of IR/HCN (4–3) and IR/HCO+(4–3), which can be taken as a proxy for the star formation efficiency (SFE) in the dense molecular gas (SFEdense), appear to be nearly independent of the dense gas fraction (fdense) for our sample of galaxies. The SFE of the total molecular gas (SFEmol) is found to increase substantially withfdensewhen combining our data with those on local (ultra)luminous infrared galaxies and high-zquasars. The mean line ratio measured for the six targeted galaxies is 0.9 ± 0.6. No significant correlation is found for the ratio with the star formation rate as traced byLIR, nor with the warm-dust temperature, for the different populations of galaxies.
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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 | 0.000 | 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".