{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:5YR46EVAWNLVUYVGLMXCQZICUS","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":"a54fc7040cf7443aafaf73a0b4cff9886f7e3642866ebdb82cb111b49122942f","cross_cats_sorted":["cs.AI","cs.LG","physics.soc-ph","q-bio.PE"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"q-bio.QM","submitted_at":"2022-08-23T14:29:04Z","title_canon_sha256":"06f25f68caa7b3c9638509e91ba25185a6d5f6bbb5b2715f22c029e67310bafe"},"schema_version":"1.0","source":{"id":"2208.11517","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2208.11517","created_at":"2026-07-05T04:51:15Z"},{"alias_kind":"arxiv_version","alias_value":"2208.11517v1","created_at":"2026-07-05T04:51:15Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2208.11517","created_at":"2026-07-05T04:51:15Z"},{"alias_kind":"pith_short_12","alias_value":"5YR46EVAWNLV","created_at":"2026-07-05T04:51:15Z"},{"alias_kind":"pith_short_16","alias_value":"5YR46EVAWNLVUYVG","created_at":"2026-07-05T04:51:15Z"},{"alias_kind":"pith_short_8","alias_value":"5YR46EVA","created_at":"2026-07-05T04:51:15Z"}],"graph_snapshots":[{"event_id":"sha256:28011e16e56953a25364ab8ac9d61eb41dde757d9714deead065844bb30dc4b1","target":"graph","created_at":"2026-07-05T04:51:15Z","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"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2208.11517/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Epidemic forecasting is the key to effective control of epidemic transmission and helps the world mitigate the crisis that threatens public health. To better understand the transmission and evolution of epidemics, we propose EpiGNN, a graph neural network-based model for epidemic forecasting. Specifically, we design a transmission risk encoding module to characterize local and global spatial effects of regions in epidemic processes and incorporate them into the model. Meanwhile, we develop a Region-Aware Graph Learner (RAGL) that takes transmission risk, geographical dependencies, and temporal","authors_text":"Bin Zhou, Feng Xie, Liang Li, Yusong Tan, Zhong Zhang","cross_cats":["cs.AI","cs.LG","physics.soc-ph","q-bio.PE"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"q-bio.QM","submitted_at":"2022-08-23T14:29:04Z","title":"EpiGNN: Exploring Spatial Transmission with Graph Neural Network for Regional Epidemic Forecasting"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2208.11517","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:a56d689537ae5e721033622dff7cc3d63c3f6dd0369ac4eae5c6d997429f7fb6","target":"record","created_at":"2026-07-05T04:51:15Z","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":"a54fc7040cf7443aafaf73a0b4cff9886f7e3642866ebdb82cb111b49122942f","cross_cats_sorted":["cs.AI","cs.LG","physics.soc-ph","q-bio.PE"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"q-bio.QM","submitted_at":"2022-08-23T14:29:04Z","title_canon_sha256":"06f25f68caa7b3c9638509e91ba25185a6d5f6bbb5b2715f22c029e67310bafe"},"schema_version":"1.0","source":{"id":"2208.11517","kind":"arxiv","version":1}},"canonical_sha256":"ee23cf12a0b3575a62a65b2e286502a4b74cb9a30d81d1fde809b53e73f513f9","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"ee23cf12a0b3575a62a65b2e286502a4b74cb9a30d81d1fde809b53e73f513f9","first_computed_at":"2026-07-05T04:51:15.923600Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T04:51:15.923600Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"pvfZ/BDcqG6shZZQolcPXq8pN10+Z4iWhCZwOGXNrk8JfhLCPpDbUPasF6Qg0J8YReXngVN+j+NK9KKjFh7GAA==","signature_status":"signed_v1","signed_at":"2026-07-05T04:51:15.923995Z","signed_message":"canonical_sha256_bytes"},"source_id":"2208.11517","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:a56d689537ae5e721033622dff7cc3d63c3f6dd0369ac4eae5c6d997429f7fb6","sha256:28011e16e56953a25364ab8ac9d61eb41dde757d9714deead065844bb30dc4b1"],"state_sha256":"9c21af7571ab816d44b994db246c9f906bcb5734077d3847ae7ace3ddaaada60"}