MID-IR LUMINOSITIES AND UV/OPTICAL STAR FORMATION RATES AT<i>z</i>< 1.4
Bibliographic record
Abstract
UV continuum and mid-IR emission constitute two widely used star formation indicators at intermediate and high redshifts. We study 2430 galaxies with z<1.4 in the Extended Groth Strip with MIPS 24 mic observations from FIDEL, spectroscopy from DEEP2, and UV, optical, and near-IR photometry from AEGIS. The data are coupled with stellar population models and Bayesian SED fitting to estimate dust-corrected SFRs. In order to probe the dust heating from stellar populations of various ages, the derived SFRs were averaged over various timescales--from 100 Myr for "current" SFR to 1--3 Gyr for long-timescale SFRs. These SED-based UV/optical SFRs are compared to total infrared luminosities extrapolated from 24 mic observations. We find that for the blue, actively star forming galaxies the correlation between the IR luminosity and the UV/optical SFR shows a decrease in scatter when going from shorter to longer SFR-averaging timescales. We interpret this as the greater role of intermediate age stellar populations in heating the dust than what is typically assumed. This holds over the entire redshift range. Many so-called green valley galaxies are simply dust-obscured actively star-forming galaxies. However, there exist 24 mic-detected galaxies, some with L>10^11 L_sun, yet with little current star formation. For them a reasonable amount of dust absorption of stellar light is sufficient to produce the observed levels of IR. In our sample optical and X-ray AGNs do not contribute on average more than ~50% to the mid-IR luminosity, and we see no evidence for a large population of "IR excess" galaxies (Abridged).
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".