Galaxy And Mass Assembly (GAMA): spectroscopic analysis
Bibliographic record
Abstract
The Galaxy And Mass Assembly (GAMA) survey is a multiwavelength photometric and spectroscopic survey, using the AAOmega spectrograph on the Anglo-Australian Telescope to obtain spectra for up to ∼300 000 galaxies over 280 deg2, to a limiting magnitude of rpet < 19.8 mag. The target galaxies are distributed over 0 < z ≲ 0.5 with a median redshift of z ≈ 0.2, although the redshift distribution includes a small number of systems, primarily quasars, at higher redshifts, up to and beyond z = 1. The redshift accuracy ranges from σv ≈ 50 km s−1 to σv ≈ 100 km s−1 depending on the signal-to-noise ratio of the spectrum. Here we describe the GAMA spectroscopic reduction and analysis pipeline. We present the steps involved in taking the raw two-dimensional spectroscopic images through to flux-calibrated one-dimensional spectra. The resulting GAMA spectra cover an observed wavelength range of 3750 ≲ λ ≲ 8850 Å at a resolution of R ≈ 1300. The final flux calibration is typically accurate to 10–20 per cent, although the reliability is worse at the extreme wavelength ends, and poorer in the blue than the red. We present details of the measurement of emission and absorption features in the GAMA spectra. These measurements are characterized through a variety of quality control analyses detailing the robustness and reliability of the measurements. We illustrate the quality of the measurements with a brief exploration of elementary emission line properties of the galaxies in the GAMA sample. We demonstrate the luminosity dependence of the Balmer decrement, consistent with previously published results, and explore further how Balmer decrement varies with galaxy mass and redshift. We also investigate the mass and redshift dependencies of the [N ii]/Hα versus [O iii]/Hβ spectral diagnostic diagram, commonly used to discriminate between star forming and nuclear activity in galaxies.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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 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".