Bhārata Strata · Maharashtra · Nashik · morphological twins
Places like cell 4870009674
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 7 distinct districts
Index confidence
0.91
GUM mean confidence of the anchor (R24)
Dimensions compared
43
morphology-v2 feature dimensions
Closest twin distance
0.311
lower = more alike (weighted)
The twins, closest first
#1 · Nashikcell 4870010339
distance 0.311
#2 · Parbhanicell 4890000934
distance 0.413 · cross-district
#3 · Nashikcell 4870009404
distance 0.481
#4 · Nashikcell 4870011928
distance 0.492
#5 · Dhulecell 4740001800
distance 0.496 · cross-district
#6 · Nashikcell 4870011461
distance 0.501
#7 · Ahmednagarcell 4660014250
distance 0.512 · cross-district
#8 · Nashikcell 4870009236
distance 0.529
#9 · Chandrapurcell 4730001120
distance 0.537 · cross-district
#10 · Sanglicell 4930002685
distance 0.539 · cross-district
#11 · Nashikcell 4870009386
distance 0.539
#12 · Nashikcell 4870007819
distance 0.541
#13 · Nashikcell 4870012243
distance 0.544
#14 · Jalgaoncell 4780001663
distance 0.553 · cross-district
#15 · Nashikcell 4870005767
distance 0.553
#16 · Nashikcell 4870012432
distance 0.554
#17 · Nashikcell 4870009503
distance 0.557
#18 · Nashikcell 4870009385
distance 0.56
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":4870009674}}}'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.