Bhārata Strata · Maharashtra · Wardha · morphological twins
Places like cell 4980002004
The MH-36 locality cells most similar to this Wardha 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 7 distinct districts
Index confidence
0.93
GUM mean confidence of the anchor (R24)
Dimensions compared
45
morphology-v2 feature dimensions
Closest twin distance
0.178
lower = more alike (weighted)
The twins, closest first
#1 · Wardhacell 4980000705
distance 0.178
#2 · Wardhacell 4980001543
distance 0.232
#3 · Wardhacell 4980002420
distance 0.234
#4 · Wardhacell 4980002971
distance 0.236
#5 · Wardhacell 4980001730
distance 0.239
#6 · Wardhacell 4980002464
distance 0.244
#7 · Yavatmalcell 5000011315
distance 0.245 · cross-district
#8 · Solapurcell 4960002357
distance 0.246 · cross-district
#9 · Jalnacell 4790003304
distance 0.249 · cross-district
#10 · Wardhacell 4980002795
distance 0.253
#11 · Wardhacell 4980003234
distance 0.254
#12 · Parbhanicell 4890002026
distance 0.255 · cross-district
#13 · Wardhacell 4980003427
distance 0.256
#14 · Wardhacell 4980001723
distance 0.261
#15 · Buldhanacell 4720004278
distance 0.263 · cross-district
#16 · Wardhacell 4980001293
distance 0.266
#17 · Amravaticell 4680002209
distance 0.267 · cross-district
#18 · Wardhacell 4980001910
distance 0.268
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":498,"cluster_id":4980002004}}}'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.