CALIFA: a diameter-selected sample for an integral field spectroscopy galaxy survey
Bibliographic record
Abstract
We describe and discuss the selection procedure and statistical properties of the galaxy sample used by the Calar Alto Legacy Integral Field Area (CALIFA) survey, a public legacy survey of 600 galaxies using integral field spectroscopy. The CALIFA “mother sample” was selected from the Sloan Digital Sky Survey (SDSS) DR7 photometric catalogue to include all galaxies with an r-band isophotal major axis between 45′′ and 79.2′′ and with a redshift 0.005 < z < 0.03. The mother sample contains 939 objects, 600 of which will be observed in the course of the CALIFA survey. The selection of targets for observations is based solely on visibility and thus keeps the statistical properties of the mother sample. By comparison with a large set of SDSS galaxies, we find that the CALIFA sample is representative of galaxies over a luminosity range of −19 > Mr > −23.1 and over a stellar mass range between 109.7 and 1011.4 M⊙. In particular, within these ranges, the diameter selection does not lead to any significant bias against – or in favour of – intrinsically large or small galaxies. Only below luminosities of Mr = −19 (or stellar masses <109.7 M⊙) is there a prevalence of galaxies with larger isophotal sizes, especially of nearly edge-on late-type galaxies, but such galaxies form <10% of the full sample. We estimate volume-corrected distribution functions in luminosities and sizes and show that these are statistically fully compatible with estimates from the full SDSS when accounting for large-scale structure. For full characterization of the sample, we also present a number of value-added quantities determined for the galaxies in the CALIFA sample. These include consistent multi-band photometry based on growth curve analyses; stellar masses; distances and quantities derived from these; morphological classifications; and an overview of available multi-wavelength photometric measurements. We also explore different ways of characterizing the environments of CALIFA galaxies, finding that the sample covers environmental conditions from the field to genuine clusters. We finally consider the expected incidence of active galactic nuclei among CALIFA galaxies given the existing pre-CALIFA data, finding that the final observed CALIFA sample will contain approximately 30 Sey2 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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.008 | 0.003 |
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".