The Relation between Globular Cluster Systems and Supermassive Black Holes in Spiral Galaxies. III. The Link to the M <sub>•</sub>–M <sub>*</sub> Correlation
Bibliographic record
Abstract
Abstract We continue to explore the relationship between the total number of globular clusters (GCs), N GC, and the central black hole mass, M •, in spiral galaxies. We present here results for the Sab galaxies NGC 3368, NGC 4736 (M94), and NGC 4826 (M64), and the Sm galaxy NGC 4395. The GC candidate selection is based on the (u* – i ′ ) versus ( i ′ – K s ) color–color diagram, and i ′ -band shape parameters. We determine the M • versus N GC correlation for these spirals, plus NGC 4258, NGC 253, M104, M81, M31, and the Milky Way. We also redetermine the correlation for the elliptical sample in Harris et al., with updated galaxy types from Sahu et al. Additionally, we derive the total stellar galaxy mass, M *, from its two-slope correlation with N GC, and fit M • versus M * for both spirals and ellipticals. We obtain log M • ∝ (1.01 ± 0.13) log N GC for ellipticals, and log M • ∝ (1.64 ± 0.24) log N GC for late-type galaxies (LTGs). The linear M • versus N GC correlation in ellipticals could be due to statistical convergence through mergers, unlike the much steeper correlation for LTGs. However, in the M • versus total stellar mass (M *) parameter space, with M * derived from its correlation with N GC, M • ∝ (1.48 ± 0.18) log M * for ellipticals, and M • ∝ (1.21 ± 0.16) log M * for LTGs. The observed agreement between ellipticals and LTGs in this parameter space may imply that black holes and galaxies coevolve through calm accretion, active galactic nuclei feedback, and other secular processes.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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".