Bibliographic record
Abstract
We present a new optical luminosity-HI mass bivariate luminosity function (BLF) based on HI line observations from the Nançay Interstellar Baryons Legacy Extragalactic Survey (NIBLES). NIBLES sources lie within the local universe (900 ≤ c z ≤ 12 000 km s−1) and were chosen from SDSS DR5 such that the optical luminosity function was sampled as uniformly as possible. The HI mass function (HIMF) derived from our raw-data BLF, which is based on HI detections only, is consistent with the HIMFs derived from other optically selected surveys in that the low-mass slope is flatter than those derived from blind HI surveys. However, spanning the entire luminosity range of NIBLES, we identify a highly consistent distribution of the HI gas mass to luminosity ratio (gas-to-light ratio) with a predictable progression in the mean MHI/L r ratio as a function of L r. This consistency allows us to construct plausible gas-to-light ratio distributions for very low-luminosity bins which lie outside the NIBLES sample. We also identify a ∼10% decrease in detection fraction for galaxies fainter than log(L r) = 9.25, consistent with the expected decrease due to distance and sensitivity effects. Accounting for these trends, we reconstruct plausible gas-to-light distributions spanning luminosity bins down to log(L r) = 5.25, thus producing a corrected BLF. This corrected BLF is in good qualitative agreement with optical luminosity-HI mass distributions from the ALFALFA survey and is able to accurately reproduce blind survey HIMFs, lending credibility that this two dimensional optical luminosity-HI mass distribution is an accurate representation of the volume density distribution of galaxies in the local universe. We also note that our agreement with HIMFs from other surveys is dependent on accounting for all systematic differences such as selection method, Hubble constant and HI flux scale.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 0.004 |
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".