MIGHTEE-H <scp>i</scp>: the first MeerKAT H <scp>i</scp> mass function from an untargeted interferometric survey
Bibliographic record
Abstract
ABSTRACT We present the first measurement of the H i mass function (HIMF) using data from MeerKAT, based on 276 direct detections from the MeerKAT International GigaHertz Tiered Extragalactic Exploration (MIGHTEE) Survey Early Science data covering a period of approximately a billion years (0 ≤ $z$ ≤ 0.084). This is the first HIMF measured using interferometric data over non-group or cluster field, i.e. a deep blank field. We constrain the parameters of the Schechter function that describes the HIMF with two different methods: $1/V_{\rm max}$ and modified maximum likelihood (MML). We find a low-mass slope $\alpha =-1.29^{+0.37}_{-0.26}$ , ‘knee’ mass $\log _{10}(M_{*}/{\rm {\rm M}_{\odot }}) = 10.07^{+0.24}_{-0.24}$ and normalization $\log _{10}(\phi _{*}/\rm Mpc^{-3})=-2.34^{+0.32}_{-0.36}$ (H0 = 67.4 km s−1 Mpc−1) for $1/V_{\rm max}$ , and $\alpha =-1.44^{+0.13}_{-0.10}$ , ‘knee’ mass $\log _{10}(M_{*}/{\rm {\rm M}_{\odot }}) = 10.22^{+0.10}_{-0.13}$ and normalization $\log _{10}(\phi _{*}/\rm Mpc^{-3})=-2.52^{+0.19}_{-0.14}$ for MML. When using $1/V_{\rm max}$ we find both the low-mass slope and ‘knee’ mass to be consistent within 1σ with previous studies based on single-dish surveys. The cosmological mass density of H i is found to be slightly larger than previously reported: $\Omega _{\rm H\,{\small I}}=5.46^{+0.94}_{-0.99} \times 10^{-4}\,h^{-1}_{67.4}$ from $1/V_{\rm max}$ and $\Omega _{\rm H\,{\small I}}=6.31^{+0.31}_{-0.31} \times 10^{-4}\,h^{-1}_{67.4}$ from MML but consistent within the uncertainties. We find no evidence for evolution of the HIMF over the last billion years.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".