WALLABY pilot survey: the Tully–Fisher relation in the NGC 4808, Vela, and NGC 5044 fields
Bibliographic record
Abstract
ABSTRACT The Tully–Fisher Relation (TFR) is a well-known empirical relationship between the luminosity of a spiral galaxy and its circular velocity, allowing us to estimate redshift independent distances. Here we use high signal-to-noise H i 21-cm integrated spectra from the second pilot data release (PDR2, 180 deg2) of the Widefield ASKAP L-band Legacy All-sky Blind surveY (WALLABY). In order to prepare for the full WALLABY survey, we have investigated the TFR in phase 2 of the pilot survey with a further three fields. The data were obtained with wide-field Phased Array Feeds on the Australian Square Kilometre Array Pathfinder (ASKAP) and have an angular resolution of 30 arcsec and a velocity resolution of $\sim$4 km s−1. Galaxy luminosities have been measured from the Wide-field Infrared Survey Explorer, and optical galaxy inclinations from the Dark Energy Camera Legacy Survey. We present TFRs for wavelengths from 0.8 to 3.4 μm. We examine sources of galaxy inclination data and investigate magnitudes from the DECam Local Volume Exploration Survey and DENIS catalogues and the 4HS target catalogue based on the VISTA Hemisphere Survey. We consider the baryonic TFR. These are all of interest for TFR using the full WALLABY survey of 200 000 galaxies. We demonstrate that WALLABY TFR distances can take their place among state-of-the-art studies of the local velocity field.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| 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".