Galaxy redshift surveys selected by neutral hydrogen using the Five-hundred metre Aperture Spherical Telescope
Bibliographic record
Abstract
We discuss the possibility of performing a substantial spectroscopic galaxy redshift survey selected via the 21-cm emission from neutral hydrogen using the Five-hundred metre Aperture Spherical Telescope (FAST) to be built in China. We consider issues related to the estimation of the source counts and optimizations of the survey, and discuss the constraints on cosmological models that such a survey could provide. We find that a survey taking around two years could detect ∼107 galaxies with an average redshift of ∼0.15 making the survey complementary to those already carried out at optical wavelengths. These conservative estimates have used the z= 0 H i mass function and have ignored the possibility of evolution. The results could be used to constrain Γ=Ωmh to 5 per cent and the spectral index, ns, to 7 per cent independent of cosmic microwave background data. If we also use simulated power spectra from the Planck satellite, we can constrain w to be within 5 per cent of −1.
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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 | 0.001 | 0.001 |
| 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) | 0.001 | 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".