{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2017:SBYKU6JXM47Z5LIHUW5PV457GQ","short_pith_number":"pith:SBYKU6JX","canonical_record":{"source":{"id":"1712.06778","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2017-12-19T04:36:24Z","cross_cats_sorted":[],"title_canon_sha256":"4f6ba14e30912c247927eda3d442336d5df2cd5ae8b7cc93688bbbe06e051324","abstract_canon_sha256":"f33446255611d8cde18a16d9f93177870c7f32572f58c19e2ec1493cbcbf8d9c"},"schema_version":"1.0"},"canonical_sha256":"9070aa7937673f9ead07a5bafaf3bf340adb27a16c846439269d1d42def93b22","source":{"kind":"arxiv","id":"1712.06778","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1712.06778","created_at":"2026-05-18T00:24:09Z"},{"alias_kind":"arxiv_version","alias_value":"1712.06778v3","created_at":"2026-05-18T00:24:09Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1712.06778","created_at":"2026-05-18T00:24:09Z"},{"alias_kind":"pith_short_12","alias_value":"SBYKU6JXM47Z","created_at":"2026-05-18T12:31:43Z"},{"alias_kind":"pith_short_16","alias_value":"SBYKU6JXM47Z5LIH","created_at":"2026-05-18T12:31:43Z"},{"alias_kind":"pith_short_8","alias_value":"SBYKU6JX","created_at":"2026-05-18T12:31:43Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2017:SBYKU6JXM47Z5LIHUW5PV457GQ","target":"record","payload":{"canonical_record":{"source":{"id":"1712.06778","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2017-12-19T04:36:24Z","cross_cats_sorted":[],"title_canon_sha256":"4f6ba14e30912c247927eda3d442336d5df2cd5ae8b7cc93688bbbe06e051324","abstract_canon_sha256":"f33446255611d8cde18a16d9f93177870c7f32572f58c19e2ec1493cbcbf8d9c"},"schema_version":"1.0"},"canonical_sha256":"9070aa7937673f9ead07a5bafaf3bf340adb27a16c846439269d1d42def93b22","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:24:09.504511Z","signature_b64":"2VG39NITGpWV6rcorLpmqO0QZ1A486K4zOjkmri4CT4/LfxZ5SnzyOrbqSrwEX6DOT+w7UnzpRX1ZqvgkL0VBA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"9070aa7937673f9ead07a5bafaf3bf340adb27a16c846439269d1d42def93b22","last_reissued_at":"2026-05-18T00:24:09.503803Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:24:09.503803Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1712.06778","source_version":3,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T00:24:09Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"MI3adANy47FrjiOG42vB/iCNdwcIxAd6DEt7cP41CjaQhc5p67x6EEiYn1sJHqcigwkolj3XSVFImchuhBczBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-23T16:26:31.104017Z"},"content_sha256":"f462c6e405e678ba5dcabcf3a1be1d96b3d80d55de99c64733953cb27a7c6d32","schema_version":"1.0","event_id":"sha256:f462c6e405e678ba5dcabcf3a1be1d96b3d80d55de99c64733953cb27a7c6d32"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2017:SBYKU6JXM47Z5LIHUW5PV457GQ","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Learning Representations from Road Network for End-to-End Urban Growth Simulation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.AI","authors_text":"Saptarshi Pal, Soumya K Ghosh","submitted_at":"2017-12-19T04:36:24Z","abstract_excerpt":"From our experiences in the past, we have seen that the growth of cities is very much dependent on the transportation networks. In mega cities, transportation networks determine to a significant extent as to where the people will move and houses will be built. Hence, transportation network data is crucial to an urban growth prediction system. Existing works have used manually derived distance based features based on the road networks to build models on urban growth. But due to the non-generic and laborious nature of the manual feature engineering process, we can shift to End-to-End systems whi"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1712.06778","kind":"arxiv","version":3},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T00:24:09Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Qeea2D3koi6JhW1yx0fz6hjf79LZY++Qn+Fl7PnO3Z8PUZkL6XJ263jZ/sy0UZ5ZiE/B3Cgwb0vPowmMHPM9CA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-23T16:26:31.104368Z"},"content_sha256":"5eaf59fc249b65f190ce5d0cb933b1ae83294ab26f468a59eee1713a7d4550b7","schema_version":"1.0","event_id":"sha256:5eaf59fc249b65f190ce5d0cb933b1ae83294ab26f468a59eee1713a7d4550b7"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/SBYKU6JXM47Z5LIHUW5PV457GQ/bundle.json","state_url":"https://pith.science/pith/SBYKU6JXM47Z5LIHUW5PV457GQ/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/SBYKU6JXM47Z5LIHUW5PV457GQ/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-06-23T16:26:31Z","links":{"resolver":"https://pith.science/pith/SBYKU6JXM47Z5LIHUW5PV457GQ","bundle":"https://pith.science/pith/SBYKU6JXM47Z5LIHUW5PV457GQ/bundle.json","state":"https://pith.science/pith/SBYKU6JXM47Z5LIHUW5PV457GQ/state.json","well_known_bundle":"https://pith.science/.well-known/pith/SBYKU6JXM47Z5LIHUW5PV457GQ/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2017:SBYKU6JXM47Z5LIHUW5PV457GQ","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":"f33446255611d8cde18a16d9f93177870c7f32572f58c19e2ec1493cbcbf8d9c","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2017-12-19T04:36:24Z","title_canon_sha256":"4f6ba14e30912c247927eda3d442336d5df2cd5ae8b7cc93688bbbe06e051324"},"schema_version":"1.0","source":{"id":"1712.06778","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1712.06778","created_at":"2026-05-18T00:24:09Z"},{"alias_kind":"arxiv_version","alias_value":"1712.06778v3","created_at":"2026-05-18T00:24:09Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1712.06778","created_at":"2026-05-18T00:24:09Z"},{"alias_kind":"pith_short_12","alias_value":"SBYKU6JXM47Z","created_at":"2026-05-18T12:31:43Z"},{"alias_kind":"pith_short_16","alias_value":"SBYKU6JXM47Z5LIH","created_at":"2026-05-18T12:31:43Z"},{"alias_kind":"pith_short_8","alias_value":"SBYKU6JX","created_at":"2026-05-18T12:31:43Z"}],"graph_snapshots":[{"event_id":"sha256:5eaf59fc249b65f190ce5d0cb933b1ae83294ab26f468a59eee1713a7d4550b7","target":"graph","created_at":"2026-05-18T00:24:09Z","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":"From our experiences in the past, we have seen that the growth of cities is very much dependent on the transportation networks. In mega cities, transportation networks determine to a significant extent as to where the people will move and houses will be built. Hence, transportation network data is crucial to an urban growth prediction system. Existing works have used manually derived distance based features based on the road networks to build models on urban growth. But due to the non-generic and laborious nature of the manual feature engineering process, we can shift to End-to-End systems whi","authors_text":"Saptarshi Pal, Soumya K Ghosh","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2017-12-19T04:36:24Z","title":"Learning Representations from Road Network for End-to-End Urban Growth Simulation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1712.06778","kind":"arxiv","version":3},"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:f462c6e405e678ba5dcabcf3a1be1d96b3d80d55de99c64733953cb27a7c6d32","target":"record","created_at":"2026-05-18T00:24:09Z","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":"f33446255611d8cde18a16d9f93177870c7f32572f58c19e2ec1493cbcbf8d9c","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2017-12-19T04:36:24Z","title_canon_sha256":"4f6ba14e30912c247927eda3d442336d5df2cd5ae8b7cc93688bbbe06e051324"},"schema_version":"1.0","source":{"id":"1712.06778","kind":"arxiv","version":3}},"canonical_sha256":"9070aa7937673f9ead07a5bafaf3bf340adb27a16c846439269d1d42def93b22","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"9070aa7937673f9ead07a5bafaf3bf340adb27a16c846439269d1d42def93b22","first_computed_at":"2026-05-18T00:24:09.503803Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:24:09.503803Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"2VG39NITGpWV6rcorLpmqO0QZ1A486K4zOjkmri4CT4/LfxZ5SnzyOrbqSrwEX6DOT+w7UnzpRX1ZqvgkL0VBA==","signature_status":"signed_v1","signed_at":"2026-05-18T00:24:09.504511Z","signed_message":"canonical_sha256_bytes"},"source_id":"1712.06778","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:f462c6e405e678ba5dcabcf3a1be1d96b3d80d55de99c64733953cb27a7c6d32","sha256:5eaf59fc249b65f190ce5d0cb933b1ae83294ab26f468a59eee1713a7d4550b7"],"state_sha256":"745ff01cb6ff19c1b40a9fd888e6874539c1848a581402341f349d4eae8a2f74"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Jmcw4cCxXtP/lu37hgpavpfpYbHRr2OCFZeeFe3lQhhjEaw0CHGKuK1no18c6KOc4MFYCM2tGfizriEYCuIuCA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-23T16:26:31.106304Z","bundle_sha256":"e16305bc0c5a064ba6b8efa1d1abb2e29b238e26f71382774710d802594fd8aa"}}