Bhārata Strata · Maharashtra · Wardha · morphological twins
Places like cell 4980003047
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 6 distinct districts
Index confidence
0.93
GUM mean confidence of the anchor (R24)
Dimensions compared
45
morphology-v2 feature dimensions
Closest twin distance
0.221
lower = more alike (weighted)
The twins, closest first
#1 · Wardhacell 4980000740
distance 0.221
#2 · Wardhacell 4980004346
distance 0.223
#3 · Wardhacell 4980000594
distance 0.224
#4 · Wardhacell 4980002198
distance 0.225
#5 · Parbhanicell 4890004817
distance 0.229 · cross-district
#6 · Wardhacell 4980001581
distance 0.229
#7 · Wardhacell 4980001563
distance 0.231
#8 · Chandrapurcell 4730008226
distance 0.231 · cross-district
#9 · Wardhacell 4980001833
distance 0.233
#10 · Wardhacell 4980002798
distance 0.233
#11 · Parbhanicell 4890005020
distance 0.234 · cross-district
#12 · Wardhacell 4980001741
distance 0.234
#13 · Nagpurcell 4840004474
distance 0.235 · cross-district
#14 · Wardhacell 4980001743
distance 0.236
#15 · Jalnacell 4790004018
distance 0.236 · cross-district
#16 · Bhandaracell 4710001238
distance 0.238 · cross-district
#17 · Wardhacell 4980001647
distance 0.239
#18 · Wardhacell 4980000798
distance 0.24
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":4980003047}}}'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.