What is the restoration method in `sdcflows` (jacobian vs least-squares)?

According to the documentation for FSL’s topup and applytopup, the tools offer two ways to (attempt to) restore voxel intensity during susceptibility distortion correction, a least-squares approach and one with Jacobian weighting/modulation: topup/ApplytopupFurtherInformation - FslWiki. Based on the release notes for 2.6.0 of sdcflows, it seems like sdcflows offers only the Jacobian approach. sdcflows/CHANGES.rst at 245648997022fabcfa218a3eb4716d7f304ba645 · nipreps/sdcflows · GitHub. Is that true, or is there also an incantation for the least-squares approach?