Abstract We present a full-sample statistical analysis of galaxy rotation curves usingthe SPARC database of 175 disk galaxies and their associated baryonic massmodeltemplates. We introduce IFM2, an effective kinematic deformation mappingthat augments the Newtonian baryonic speed template through (i) a controlled innermodulation and (ii) an outer saturating boundary term that yields asymptotically flatprofiles without specifying a microscopic halo-density parametrization. We performlikelihood-based inference on a galaxy-by-galaxy basis and summarize the recoveredparameters in a population framework, reporting empirical hyperparameter estimatesas a reproducible initialization for future full hierarchical evidence calculations.We benchmark IFM2 against NFW halo fits and an RAR-based phenomenologicalmapping using reduced 𝜒2𝜈, AIC, BIC, and blocked 𝐾-fold cross-validation, and wereport representative uncertainty structure across a dynamical cross-section of thesample. Because unusually small 𝜒2𝜈values can reflect either model flexibility or mismatcheduncertainty structure, we emphasize out-of-sample diagnostics and providecorrelated-error stress tests using radial covariance kernels, together with uncertaintybudgetsensitivity summaries. IFM2 is formulated with an observer-anchored measurementboundary condition that does not imply spatial privilege or cosmologicalcentrality and is consistent with the Copernican principle.Interpretation is kept disciplined: IFM2 is explored as an effective phenomenologicaldescription of missing-mass signatures at galaxy scales. Physical attributionis treated explicitly as a falsifiable hypothesis rather than an inference from rotationcurvefits alone. We distinguish (Level 1) predictive performance under stated likelihoodassumptions and (Level 2) population regularities within SPARC from (Level 3)microphysical interpretation, which requires independent probes (e.g., joint lensing–dynamics constraints and matched-sample tests against hydrodynamical simulations).We discuss post-galaxy consistency checks as conservative, non-decisive stress testsand identify decisive next steps at cluster and large-scale-structure scales.
Ammar Nasir Hussein al-mantafji (Mon,) studied this question.