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Record W4309134926 · doi:10.1017/pasa.2022.43

WALLABY Pilot Survey: Public release of HI kinematic models for more than 100 galaxies from phase 1 of ASKAP pilot observations

2022· article· en· W4309134926 on OpenAlexaff
Nathan Deg, Kristine Spekkens, T. Westmeier, T. Reynolds, P. Venkataraman, S. Goliath, Ao Shen, R. Halloran, A. Bosma, Barbara Catinella, W. J. G. de Blok, Helga Dénes, E. M. DiTeodoro, Ahmed Elagali, Bi‐Qing For, Cullan Howlett, G. I. G. Józsa, P. Kamphuis, D. Kleiner, B. Koribalski, K. Lee-Waddell, Federico Lelli, X. Lin, C. Murugeshan, Se–Heon Oh, J. Rhee, T. C. Scott, L. Staveley‐Smith, J. M. van der Hulst, L. Verdes‐Montenegro, Jing Wang, O. Ivy Wong

Bibliographic record

VenuePublications of the Astronomical Society of Australia · 2022
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAstronomy and Astrophysical Research
Canadian institutionsCanadian Institute for Theoretical AstrophysicsHerzberg Institute of AstrophysicsUniversity of TorontoRoyal Military College of CanadaQueen's University
FundersMinistry of Science and ICT, South KoreaMinistério da Ciência, Tecnologia e Ensino SuperiorFundação para a Ciência e a TecnologiaNational Research Foundation of KoreaUniversidade do PortoNational Research Foundation
KeywordsPhysicsGalaxyKinematicsAstrophysicsPhase (matter)Active galactic nucleusAstronomyClassical mechanics

Abstract

fetched live from OpenAlex

Abstract We present the Widefield ASKAP L-band Legacy All-sky Blind surveY (WALLABY) Pilot Phase I H i kinematic models. This first data release consists of H i observations of three fields in the direction of the Hydra and Norma clusters, and the NGC 4636 galaxy group. In this paper, we describe how we generate and publicly release flat-disk tilted-ring kinematic models for 109/592 unique H i detections in these fields. The modelling method adopted here—which we call the WALLABY Kinematic Analysis Proto-Pipeline (WKAPP) and for which the corresponding scripts are also publicly available—consists of combining results from the homogeneous application of the FAT and 3DBarolo algorithms to the subset of 209 detections with sufficient resolution and $S/N$ in order to generate optimised model parameters and uncertainties. The 109 models presented here tend to be gas rich detections resolved by at least 3–4 synthesised beams across their major axes, but there is no obvious environmental bias in the modelling. The data release described here is the first step towards the derivation of similar products for thousands of spatially resolved WALLABY detections via a dedicated kinematic pipeline. Such a large publicly available and homogeneously analysed dataset will be a powerful legacy product that that will enable a wide range of scientific studies.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.061
Threshold uncertainty score0.818

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.198
GPT teacher head0.353
Teacher spread0.155 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations18
Published2022
Admission routes1
Has abstractyes

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