Preprint typeset using L ATEX style emulateapj v. 11/12/01 [OII] AS A STAR FORMATION RATE INDICATOR
Bibliographic record
Abstract
We investigate the [O II] emission-line as a star formation rate (SFR) indicator using integrated spectra of 97 galaxies from the Nearby Field Galaxies Survey (NFGS). The sample includes all Hubble types and contains SFRs ranging from 0.01 to 100 M ⊙ yr −1. We compare the Kennicutt [O II] and Hα SFR calibrations and show that there are two significant effects which produce disagreement between SFR([O II]) and SFR(Hα): reddening and metallicity. Differences in the ionization state of the ISM do not contribute significantly to the observed difference between SFR([O II]) and SFR(Hα) for the NFGS galaxies with metallicities log(O/H) + 12 � 8.5. The Kennicutt [O II]–SFR relation assumes a typical reddening for nearby galaxies; in practice, the reddening differs significantly from sample to sample. We derive a new SFR([O II]) calibration which does not contain a reddening assumption. Our new SFR([O II]) calibration also provides an optional correction for metallicity. Our SFRs derived from [O II] agree with those derived from Hα to within 0.03-0.05 dex. We show that the reddening, E(B −V), increases with intrinsic (i.e. reddening corrected) [O II] luminosity for the NFGS sample. We apply our SFR([O II]) calibration with metallicity correction to two samples: high-redshift 0.8 < z < 1.6 galaxies from the NICMOS Hα survey, and 0.5 < z < 1.1 galaxies from the Canada-France Redshift Survey. The SFR([O II]) and SFR(Hα) for these samples agree to within the scatter observed for the NFGS sample, indicating that our SFR([O II]) relation can be applied to both local and high-z galaxies. Finally, we apply our SFR([O II]) to estimates of the cosmic star formation history. After reddening and metallicity corrections, the star formation rate densities derived from [O II] and Hα agree to within ∼ 30%. Subject headings: galaxies:starburst–galaxies:abundances–galaxies:fundamental parameters–galaxies:high-redshift
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.722 | 0.699 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".