WALLABY pre-pilot and pilot survey: The Tully Fisher relation in Eridanus, Hydra, Norma, and NGC4636 fields
Bibliographic record
Abstract
ABSTRACT The WALLABY pilot survey has been conducted using the Australian SKA Pathfinder (ASKAP). The integrated 21-cm H i line spectra are formed in a very different manner compared to usual single-dish spectra Tully–Fisher measurements. It is thus extremely important to ensure that slight differences (e.g. biases due to missing flux) are quantified and understood in order to maximise the use of the large amount of data becoming available soon. This article is based on four fields for which the data are scientifically interesting by themselves. The pilot data discussed here consist of 614 galaxy spectra at a rest wavelength of 21 cm. Of these spectra, 472 are of high enough quality to be used to potentially derive distances using the Tully–Fisher relation. We further restrict the sample to the 251 galaxies whose inclination is sufficiently close to edge-on. For these, we derive Tully–Fisher distances using the deprojected WALLABY velocity widths combined with infrared (WISE W1) magnitudes. The resulting Tully–Fisher distances for the Eridanus, Hydra, Norma, and NGC4636 clusters are 21.5, 53.5, 69.4, and 23.0 Mpc, respectively, with uncertainties of 5–10 per cent, which are better or equivalent to the ones obtained in studies using data obtained with giant single dish telescopes. The pilot survey data show the benefits of WALLABY over previous giant single-dish telescope surveys. WALLABY is expected to detect around half a million galaxies with a mean redshift of $z = 0.05 (200\, \mathrm{Mpc})$. This study suggests that about 200 000 Tully–Fisher distances might result from the survey.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".