{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2017:TPNRSFIYH6XPKO3ECFHRUSJ6W2","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"fa4fea1b07d1f674635a07562b64a497638f254a95911944542d6bcb0d8f8cc6","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.AP","submitted_at":"2017-09-01T17:40:21Z","title_canon_sha256":"7162360bc3229058052bbc3d10f04f5568365b4029bdb7685bc1740044e1a404"},"schema_version":"1.0","source":{"id":"1709.00399","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1709.00399","created_at":"2026-05-18T00:36:10Z"},{"alias_kind":"arxiv_version","alias_value":"1709.00399v1","created_at":"2026-05-18T00:36:10Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1709.00399","created_at":"2026-05-18T00:36:10Z"},{"alias_kind":"pith_short_12","alias_value":"TPNRSFIYH6XP","created_at":"2026-05-18T12:31:46Z"},{"alias_kind":"pith_short_16","alias_value":"TPNRSFIYH6XPKO3E","created_at":"2026-05-18T12:31:46Z"},{"alias_kind":"pith_short_8","alias_value":"TPNRSFIY","created_at":"2026-05-18T12:31:46Z"}],"graph_snapshots":[{"event_id":"sha256:f46f0cd384fee3e9faac3edb07ea4a2e7280fab70294534961cbdd9bb31a5a22","target":"graph","created_at":"2026-05-18T00:36:10Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"paper":{"abstract_excerpt":"Simulation of rainfall over a region for long time-sequences can be very useful for planning and policy-making, especially in India where the economy is heavily reliant on monsoon rainfall. However, such simulations should be able to preserve the known spatial and temporal characteristics of rainfall over India. General Circulation Models (GCMs) are unable to do so, and various rainfall generators designed by hydrologists using stochastic processes like Gaussian Processes are also difficult to apply over the vast and highly diverse landscape of India. In this paper, we explore a series of Baye","authors_text":"Adway Mitra","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.AP","submitted_at":"2017-09-01T17:40:21Z","title":"Bayesian approach to Spatio-temporally Consistent Simulation of Daily Monsoon Rainfall over India"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1709.00399","kind":"arxiv","version":1},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:68d9a7842c29d4a7674a40c166af188581eabf881e74198a96c62cca32f63b81","target":"record","created_at":"2026-05-18T00:36:10Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"fa4fea1b07d1f674635a07562b64a497638f254a95911944542d6bcb0d8f8cc6","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.AP","submitted_at":"2017-09-01T17:40:21Z","title_canon_sha256":"7162360bc3229058052bbc3d10f04f5568365b4029bdb7685bc1740044e1a404"},"schema_version":"1.0","source":{"id":"1709.00399","kind":"arxiv","version":1}},"canonical_sha256":"9bdb1915183faef53b64114f1a493eb6b0f329e5266f6e93bb57649ec563aa10","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"9bdb1915183faef53b64114f1a493eb6b0f329e5266f6e93bb57649ec563aa10","first_computed_at":"2026-05-18T00:36:10.460722Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:36:10.460722Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"7BgVFn39FNN6zxPUg0FdRWk7oxfwYVCAKSHaeFq8Iu7heM7TahXboCaiiFX3dZ+8p7giJ21oLFjGGwVzPXxfBg==","signature_status":"signed_v1","signed_at":"2026-05-18T00:36:10.461372Z","signed_message":"canonical_sha256_bytes"},"source_id":"1709.00399","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:68d9a7842c29d4a7674a40c166af188581eabf881e74198a96c62cca32f63b81","sha256:f46f0cd384fee3e9faac3edb07ea4a2e7280fab70294534961cbdd9bb31a5a22"],"state_sha256":"d79e0cd32ddb40527a8ca13b1993bec4db3bd1e54c936cea013fc6bf3a34a76c"}