H <scp>i</scp>-MaNGA: tracing the physics of the neutral and ionized ISM with the second data release
Bibliographic record
Abstract
ABSTRACT We present the second data release for the H i-MaNGA programme of H i follow-up observations for the SDSS-IV MaNGA survey. This release contains measurements for 3669 unique galaxies, combining 2108 Green Bank Telescope observations with an updated crossmatch of the MaNGA sample with the ALFALFA survey. We combine these data with MaNGA spectroscopic measurements to examine relationships between H i-to-stellar mass ratio (${\rm M_{H\, {\small I}}/{M_*}}$) and average ISM/star formation properties probed by optical emission lines. ${\rm M_{H\, {\small I}}/{M_*}}$ is very weakly correlated with the equivalent width of H α, implying a loose connection between the instantaneous star formation rate and the H i reservoir, although the link between ${\rm M_{H\, {\small I}}/{M_*}}$ and star formation strengthens when averaged even over only moderate time-scales (∼30 Myr). Galaxies with elevated H i depletion times have enhanced [O i]/H α and depressed H α surface brightness, consistent with more H i residing in a diffuse and/or shock-heated phase that is less capable of condensing into molecular clouds. Of all optical lines, ${\rm M_{H\, {\small I}}/{M_*}}$ correlates most strongly with oxygen equivalent width, EW(O), which is likely a result of the existing correlation between ${\rm M_{H\, {\small I}}/{M_*}}$ and gas-phase metallicity. Residuals in the ${\rm M_{H\, {\small I}}/{M_*}}$−EW(O) relation are again correlated with [O i]/H α and H α surface brightness, suggesting they are also driven by variations in the fraction of diffuse and/or shock-heated gas. We recover the strong anticorrelation between ${\rm M_{H\, {\small I}}/{M_*}}$ and gas-phase metallicity seen in previous studies. We also find a relationship between ${\rm M_{H\, {\small I}}/{M_*}}$ and [O i]6302/H α, suggesting that higher fractions of diffuse and/or shock-heated gas are more prevalent in gas-rich galaxies.
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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 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 0.006 |
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".