On the H <scp>i</scp> Content of MaNGA Major Merger Pairs
Bibliographic record
Abstract
Abstract To study the role of H i content in galaxy interactions, we select galaxy pairs and control galaxies from the SDSS-IV MaNGA IFU survey, adopting kinematic asymmetry as a new effective indicator to describe the merger stage. With archival data from the HI-MaNGA survey and new observations from the Five-hundred-meter Aperture Spherical radio Telescope (FAST), we investigate the differences in H i gas fraction (fH i), star formation rate (SFR), and H i star formation efficiency (SFEH i) between pairs and controls. Our results suggest that on average the H i gas fraction of major-merger pairs is marginally decreased by ∼ 15% relative to isolated galaxies, and paired galaxies during pericentric passage show weakly decreased fH i (−0.10 ± 0.05 dex), significantly enhanced SFR (0.42 ± 0.11 dex), and SFEH i (0.48 ± 0.12 dex). We propose the marginally detected H i depletion may originate from the gas consumption in fueling the enhanced H2 reservoir of galaxy pairs.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".