Star Formation Rates in Resolved Galaxies: Calibrations with Near and Far Infrared Data for NGC5055 and NGC6946 1
Bibliographic record
Abstract
We use the near-infrared Br{$γ$} hydrogen recombination line as a reference star formation rate (SFR) indicator to test the validity and establish the calibration of the Herschel/PACS 70 {$μ$}m emission as a SFR tracer for sub-galactic regions in external galaxies. Br{$γ$} offers the double advantage of directly tracing ionizing photons and of being relatively insensitive to the effects of dust attenuation. For our first experiment, we use archival Canada-France-Hawaii Telescope Br{$γ$} and Ks images of two nearby galaxies: NGC 5055 and NGC 6946, which are also part of the Herschel program KINGFISH (Key Insights on Nearby Galaxies: a Far-Infrared Survey with Herschel). We use the extinction corrected Br{$γ$} emission to derive the SFR(70) calibration for H II regions in these two galaxies. A comparison of the SFR(70) calibrations at different spatial scales, from 200 pc to the size of the whole galaxy, reveals that about 50% of the total 70 {$μ$}m emission is due to dust heated by stellar populations that are unrelated to the current star formation. We use a simple model to qualitatively relate the increase of the SFR(70) calibration coefficient with decreasing region size to the star formation timescale. We provide a calibration for an unbiased SFR indicator that combines the observed H{$α$} with the 70 {$μ$}m emission, also for use in H II regions. We briefly analyze the PACS 100 and 160 {$μ$}m maps and find that longer wavelengths are not as good SFR indicators as 70 {$μ$}m, in agreement with previous results. We find that the calibrations show about 50% difference between the two galaxies, possibly due to effects of inclination. Based on observations obtained with WIRCam, a joint project of CFHT, Taiwan, Korea, Canada, France, and the Canada-France-Hawaii Telescope (CFHT) which is operated by the National Research Council (NRC) of Canada, the Institute National des Sciences de l'Univers of the Centre National de la Recherche Scientifique of France, and the University of Hawaii.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".