Pre-existing dwarfs, tidal knots and a tidal dwarf galaxy: an unbiased H <scp>i</scp>study of the gas-rich interacting galaxy group NGC 3166/9
Bibliographic record
Abstract
We present Arecibo Legacy Fast ALFA (ALFALFA) and follow-up Giant Metrewave Radio Telescope (GMRT) H i observations of the gas-rich interacting group NGC 3166/9. The sensitive ALFALFA data provide a complete census of H i-bearing systems in the group while the high-resolution GMRT data elucidate their origin, enabling one of the first unbiased physical studies of gas-rich dwarf companions and the subsequent identification of second-generation, tidal dwarf galaxies in a nearby group. The ALFALFA maps reveal an extended H i envelope around the NGC 3166/9 group core, which we mosaic at higher resolution using six GMRT pointings spanning ∼1 deg2. A thorough search of the GMRT data cube reveals eight low-mass objects with gas masses ranging from 4 × 107 to 3 × 108 M⊙ and total dynamical masses up to 1.4 × 109 M⊙. A comparison of the H i fluxes measured from the GMRT data to those measured in the ALFALFA data suggests that a significant fraction (∼60 per cent) of the H i is smoothly distributed on scales greater than 1 arcmin (∼7 kpc at the NGC 3166/9 distance). We compute stellar masses and star formation rates for the eight low-mass GMRT detections, using ancillary Sloan Digital Sky Survey (SDSS) and Galaxy Evolution Explorer (GALEX) data, and use these values to constrain their origin. Most of the detections are likely to be either pre-existing dwarf irregular galaxies or short-lived, tidally formed knots; however, one candidate, AGC 208457, is clearly associated with a tidal tail extending below NGC 3166, exhibits a dynamical to gas mass ratio close to unity and has a stellar content and star formation rate that are broadly consistent with both simulated as well as candidate tidal dwarf galaxies from the literature. Our observations therefore strongly suggest that AGC 208457 is a tidal dwarf galaxy.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.001 | 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".