The Spectroscopy and H-band Imaging of Virgo Cluster Galaxies (SHIVir) Survey: Scaling Relations and the Stellar-to-total Mass Relation
Bibliographic record
Abstract
Abstract We present parameter distributions and fundamental scaling relations for 190 Virgo cluster galaxies in the SHIVir survey. The distribution of galaxy velocities is bimodal about V circ ∼ 125 km s−1, hinting at the existence of dynamically unstable modes in the inner regions of galaxies. An analysis of the Tully-Fisher relation (TFR) of late-type galaxies (LTGs) and the fundamental plane (FP) of early-type galaxies (ETGs) is presented, yielding a compendium of galaxy scaling relations. The slope and zero-point of the Virgo TFR match those of field galaxies, while scatter differences likely reflect distinct evolutionary histories. The velocities minimizing scatter for the TFR and FP are measured at large apertures where the baryonic fraction becomes subdominant. While TFR residuals remain independent of any galaxy parameters, FP residuals (i.e., the FP “tilt”) correlate strongly with the dynamical-to-stellar mass ratio, yielding stringent galaxy formation constraints. We construct a stellar-to-total mass relation (STMR) for ETGs and LTGs and find linear but distinct trends over the range M * = 108–11 M ⊙. Stellar-to-halo mass relations (SHMRs), which probe the extended dark matter halo, can be scaled down to masses estimated within the optical radius, showing a tight match with the Virgo STMR at low masses; possibly inadequate halo abundance matching prescriptions and broad radial scalings complicate this comparison at all masses. While ETGs appear to be more compact than LTGs of the same stellar mass in projected space, their mass-size relations in physical space are identical. The trends reported here may soon be validated through well-resolved numerical simulations.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".