Bhārata Strata · Maharashtra · Dharashiv · morphological twins
Places like cell 4880001294
The MH-36 locality cells most similar to this Dharashiv cell across terrain, built form, land cover, climate dynamics and connectivity — ranked by a GUM-confidence-weighted (R24) distance, with the temporal block down-weighted. Each twin is a real cell with its own witnessed dossier.
Twins found
18
across 4 distinct districts
Index confidence
0.93
GUM mean confidence of the anchor (R24)
Dimensions compared
44
morphology-v2 feature dimensions
Closest twin distance
0.147
lower = more alike (weighted)
The twins, closest first
#1 · Dharashivcell 4880001209
distance 0.147
#2 · Dharashivcell 4880001293
distance 0.164
#3 · Dharashivcell 4880001920
distance 0.172
#4 · Dharashivcell 4880002228
distance 0.174
#5 · Sanglicell 4930003652
distance 0.176 · cross-district
#6 · Sanglicell 4930002444
distance 0.177 · cross-district
#7 · Dharashivcell 4880001205
distance 0.177
#8 · Dharashivcell 4880001295
distance 0.18
#9 · Dharashivcell 4880001813
distance 0.185
#10 · Dharashivcell 4880001296
distance 0.19
#11 · Dharashivcell 4880001919
distance 0.194
#12 · Dharashivcell 4880001832
distance 0.197
#13 · Dharashivcell 4880000226
distance 0.2
#14 · Washimcell 4990003067
distance 0.201 · cross-district
#15 · Dharashivcell 4880001734
distance 0.202
#16 · Beedcell 4700006878
distance 0.202 · cross-district
#17 · Dharashivcell 4880002060
distance 0.203
#18 · Dharashivcell 4880002467
distance 0.203
witness: find_twins — morphology-twin-index-v2 (R24, GUM-confidence-weighted, magnitude-aware, temporal block down-weighted). Distance is the weighted feature distance; lower is more alike. Cross-district twins are the discriminative signal.
Re-witness these twins
curl -s https://api.gridrock.ai/mcp -H 'Content-Type: application/json' \
-H 'Accept: application/json, text/event-stream' \
-d '{"jsonrpc":"2.0","id":1,"method":"tools/call","params":{"name":"find_twins",
"arguments":{"admin_code":488,"cluster_id":4880001294}}}'Scope: the live MH-36 cube. Twins are computed from the sha-verified morphology-v2 vector; the engine supplies no goodness/suitability ranking — only morphological similarity.