Bhārata Strata · Maharashtra · Pune · morphological twins
Places like cell 4900006023
The MH-36 locality cells most similar to this Pune 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 5 distinct districts
Index confidence
0.91
GUM mean confidence of the anchor (R24)
Dimensions compared
45
morphology-v2 feature dimensions
Closest twin distance
0.295
lower = more alike (weighted)
The twins, closest first
#1 · Sanglicell 4930006918
distance 0.295 · cross-district
#2 · Punecell 4900006136
distance 0.302
#3 · Punecell 4900005777
distance 0.35
#4 · Sataracell 4940008573
distance 0.357 · cross-district
#5 · Punecell 4900003300
distance 0.378
#6 · Punecell 4900001858
distance 0.401
#7 · Punecell 4900005520
distance 0.403
#8 · Sataracell 4940007438
distance 0.405 · cross-district
#9 · Nashikcell 4870003968
distance 0.423 · cross-district
#10 · Solapurcell 4960009487
distance 0.431 · cross-district
#11 · Sataracell 4940007544
distance 0.44 · cross-district
#12 · Punecell 4900005776
distance 0.453
#13 · Sanglicell 4930000248
distance 0.46 · cross-district
#14 · Punecell 4900006024
distance 0.465
#15 · Sanglicell 4930000293
distance 0.469 · cross-district
#16 · Punecell 4900012218
distance 0.472
#17 · Punecell 4900008398
distance 0.473
#18 · Punecell 4900010017
distance 0.474
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":490,"cluster_id":4900006023}}}'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.