Where literal substrate disagrees with library-free structure-space — and which dimensions hold any two apart.
Every image is a displacement vector from a fixed geometric origin, across the full VCLIG battery, scaled by each axis's geometric range — no learned population. NCD asks whether two images share compressible substrate. VTL asks whether they organize space similarly. The useful cases are often the disagreements.
showing inlined sample · 7 images
Collection summaryhow the full set divides across the NCD / VTL crossing
Distance matrixdarker green = structurally closer · darker red = farther · click a cell for drivers
structural kinship case — far by substrate (NCD), near by structure (VTL)
Disagreement mapx = substrate farness rank · y = VTL farness rank · lower right is structural kinship
Top structural kinship
Highest disagreement
Closest VTL pairs
Farthest VTL pairs
Displacement from originmagnitude of each image's position vector — how far from the structural zero
Nearest neighborwho each image is structurally closest to — the cluster structure