Bhārata Strata · Maharashtra · Dhule · morphological twins
Places like cell 4740003710
The MH-36 locality cells most similar to this Dhule 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 3 distinct districts
Index confidence
0.92
GUM mean confidence of the anchor (R24)
Dimensions compared
44
morphology-v2 feature dimensions
Closest twin distance
0.094
lower = more alike (weighted)
The twins, closest first
#1 · Dhulecell 4740003880
distance 0.094
#2 · Dhulecell 4740003874
distance 0.143
#3 · Dhulecell 4740003968
distance 0.161
#4 · Nashikcell 4870011477
distance 0.163 · cross-district
#5 · Dhulecell 4740004767
distance 0.164
#6 · Jalgaoncell 4780007260
distance 0.174 · cross-district
#7 · Jalgaoncell 4780004220
distance 0.179 · cross-district
#8 · Jalgaoncell 4780005854
distance 0.179 · cross-district
#9 · Dhulecell 4740003459
distance 0.18
#10 · Dhulecell 4740003875
distance 0.182
#11 · Jalgaoncell 4780008684
distance 0.182 · cross-district
#12 · Dhulecell 4740004293
distance 0.183
#13 · Jalgaoncell 4780007383
distance 0.185 · cross-district
#14 · Dhulecell 4740004382
distance 0.185
#15 · Dhulecell 4740002545
distance 0.186
#16 · Jalgaoncell 4780007163
distance 0.189 · cross-district
#17 · Dhulecell 4740000252
distance 0.195
#18 · Dhulecell 4740003967
distance 0.195
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":474,"cluster_id":4740003710}}}'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.