The inner mass distribution of late-type spiral galaxies from<tt>SAURON</tt>stellar kinematic maps
Bibliographic record
Abstract
We infer the central mass distributions within 0.4-1.2 disc scalelengths of 18 late-type spiral galaxies using two different dynamical modelling approaches - the asymmetric drift correction (ADC) and axisymmetric Jeans anisotropic multi-Gaussian expansion (JAM) model. ADC adopts a thin-disc assumption, whereas JAM does a full line-of-sight velocity integration. We use stellar kinematics maps obtained with the integral-field spectrograph {SAURON} to derive the corresponding circular velocity curves from the two models. To find their best-fitting values, we apply the Markov Chain Monte Carlo (MCMC) method. ADC and JAM modelling approaches are consistent within 5 per cent uncertainty when the ordered motions are significant comparable to the random motions, I.e. overline{v_{φ }}/σ _R is locally greater than 1.5. Below this value, the ratio vc, JAM/vc, ADC gradually increases with decreasing overline{v_{φ }}/σ _R, reaching vc,JAM ≈ 2 × vc, ADC. Such conditions indicate that the stellar masses of the galaxies in our sample are not confined to their disc planes and likely have a non-negligible contribution from their bulges and thick discs.
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 | 0.000 | 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".