Robustness addendum evaluates stability of VES SPARC Stage 5B improvements in galaxy data, suggesting reliability of findings.
This robustness addendum extends the frozen VES Stage 5B SPARC diagnostic analysis by testing whether the reported improvement over a fixed baryonic baseline is stable under galaxy-level resampling and metadata-score perturbations. The analysis uses the released metadata-merged Stage 5B table and evaluates the per-galaxy quantity ΔRMSE = RMSE(Stage5B) − RMSE(baryon), where negative values indicate improvement over the frozen baryonic baseline. Three diagnostic tests are performed: 10,000 bootstrap resamples of the galaxy-level ΔRMSE distribution, leave-one-galaxy-out jackknife resampling, and 5,000 Monte Carlo perturbations of the empirical Q_meta purity-score weights by ±30 percent followed by renormalization. In the metadata-clean subset of 94 galaxies, the bootstrap mean ΔRMSE remains strongly negative, with a 95 percent confidence interval of approximately [−11.22, −8.71]. The bootstrap median interval is also fully negative. In the medium-risk subset of 78 galaxies, the mean ΔRMSE remains negative with a 95 percent confidence interval of approximately [−3.80, −2.50]. Jackknife tests show that the mean improvement is not driven by any single dominant galaxy. The Q_meta sensitivity test shows that the clean-subset improvement fraction remains equal to 1.0 across all tested weight perturbations, while the clean median ΔRMSE remains stably negative. The remaining failures are concentrated in systems with baryonic inner overshoot, sparse rotation-curve sampling, low SPARC quality, or elevated metadata reconstruction risk. These results strengthen the empirical status of VES Stage 5B as a statistically robust frozen diagnostic model on the SPARC clean and medium-risk subsets. They do not constitute physical validation of VES and do not replace direct comparison against RAR/MOND-like relations, NFW or Burkert halo baselines, variable mass-to-light ratio tests, or a full elliptic/radial field solver.
No takes yet. Share an insight, caveat, or question.
Mikheil Rusishvili (2026) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: