WALLABY Pilot Survey: H <scp>i</scp> gas kinematics of galaxy pairs in cluster environment
Bibliographic record
Abstract
ABSTRACT We examine the H i gas kinematics of galaxy pairs in two clusters and a group using Australian Square Kilometre Array Pathfinder (ASKAP) WALLABY pilot survey observations. We compare the H i properties of galaxy pair candidates in the Hydra I and Norma clusters, and the NGC 4636 group, with those of non-paired control galaxies selected in the same fields. We perform H i profile decomposition of the sample galaxies using a tool, baygaud, which allows us to deblend a line-of-sight velocity profile with an optimal number of Gaussian components. We construct H i superprofiles of the sample galaxies via stacking of their line profiles after aligning the central velocities. We fit a double Gaussian model to the superprofiles and classify them as kinematically narrow and broad components with respect to their velocity dispersions. Additionally, we investigate the gravitational instability of H i gas discs of the sample galaxies using Toomre Q parameters and H i morphological disturbances. We investigate the effect of the cluster environment on the H i properties of galaxy pairs by dividing the cluster environment into three subcluster regions (i.e. outskirts, infalling, and central regions). We find that the denser cluster environment (i.e. infalling and central regions) is likely to impact the H i gas properties of galaxies in a way of decreasing the amplitude of the kinematically narrow H i gas ($M_{\rm {narrow}}^{\rm {H\, \small {\rm I}}}$/$M_{\rm {total}}^{\rm {H\, \small {\rm I}}}$), and increasing the Toomre Q values of the infalling and central galaxies. This tendency is likely to be more enhanced for galaxy pairs in the cluster environment.
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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 | 0.000 | 0.000 |
| 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 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".