Bhārata Strata · Maharashtra · Nashik · morphological twins
Places like cell 4870008613
The MH-36 locality cells most similar to this Nashik 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
0.9
GUM mean confidence of the anchor (R24)
Dimensions compared
43
morphology-v2 feature dimensions
Closest twin distance
0.144
lower = more alike (weighted)
The twins, closest first
#1 · Nashikcell 4870008467
distance 0.144
#2 · Nashikcell 4870008758
distance 0.179
#3 · Nashikcell 4870008612
distance 0.189
#4 · Nashikcell 4870009730
distance 0.288
#5 · Nashikcell 4870008456
distance 0.29
#6 · Nashikcell 4870008749
distance 0.303
#7 · Nashikcell 4870010515
distance 0.313
#8 · Nashikcell 4870008318
distance 0.316
#9 · Nashikcell 4870010772
distance 0.321
#10 · Nashikcell 4870008887
distance 0.325
#11 · Nandurbarcell 4860000343
distance 0.325 · cross-district
#12 · Nashikcell 4870008310
distance 0.339
#13 · Nandurbarcell 4860000225
distance 0.341 · cross-district
#14 · Ratnagiricell 4920003287
distance 0.342 · cross-district
#15 · Dhulecell 4740003553
distance 0.342 · cross-district
#16 · Nandurbarcell 4860000262
distance 0.343 · cross-district
#17 · Dhulecell 4740003552
distance 0.344 · cross-district
#18 · Nashikcell 4870008755
distance 0.348
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":487,"cluster_id":4870008613}}}'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.