{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:GVXNNUEEUYTHCUMS7INVDD5WZB","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":"8319ef04ab93e994533f5af853e1b81342fe716243f726f9549ce2c0ec4b6164","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-08-25T10:22:03Z","title_canon_sha256":"ba5a15e686d513edd61159bdbd10694253b127aa6aec1aca1482853a478094fb"},"schema_version":"1.0","source":{"id":"2508.17867","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2508.17867","created_at":"2026-07-05T11:59:21Z"},{"alias_kind":"arxiv_version","alias_value":"2508.17867v2","created_at":"2026-07-05T11:59:21Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2508.17867","created_at":"2026-07-05T11:59:21Z"},{"alias_kind":"pith_short_12","alias_value":"GVXNNUEEUYTH","created_at":"2026-07-05T11:59:21Z"},{"alias_kind":"pith_short_16","alias_value":"GVXNNUEEUYTHCUMS","created_at":"2026-07-05T11:59:21Z"},{"alias_kind":"pith_short_8","alias_value":"GVXNNUEE","created_at":"2026-07-05T11:59:21Z"}],"graph_snapshots":[{"event_id":"sha256:0dcadb96e50ba456c03448e39541a08e33a5a42b0142afe60540ceb8ebbd5bd4","target":"graph","created_at":"2026-07-05T11:59:21Z","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/2508.17867/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Accurate air quality prediction is becoming increasingly important in the environmental field. To address issues such as low prediction accuracy and slow real-time updates in existing models, which lead to lagging prediction results, we propose a Transformer-based spatiotemporal data prediction method (Ada-TransGNN) that integrates global spatial semantics and temporal behavior. The model constructs an efficient and collaborative spatiotemporal block set comprising a multi-head attention mechanism and a graph convolutional network to extract dynamically changing spatiotemporal dependency featu","authors_text":"Dan Wang, Feng Jiang, Zhanquan Wang","cross_cats":["cs.AI"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-08-25T10:22:03Z","title":"Ada-TransGNN: An Air Quality Prediction Model Based On Adaptive Graph Convolutional Networks"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2508.17867","kind":"arxiv","version":2},"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":"sha256:26f6e109033539a7bbaa49aa120c787caa2b47c306dff5983c4c9b3ee6ab6674","target":"record","created_at":"2026-07-05T11:59:21Z","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":"8319ef04ab93e994533f5af853e1b81342fe716243f726f9549ce2c0ec4b6164","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-08-25T10:22:03Z","title_canon_sha256":"ba5a15e686d513edd61159bdbd10694253b127aa6aec1aca1482853a478094fb"},"schema_version":"1.0","source":{"id":"2508.17867","kind":"arxiv","version":2}},"canonical_sha256":"356ed6d084a626715192fa1b518fb6c8727a482328fc97157cd8d0b307d26cbb","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"356ed6d084a626715192fa1b518fb6c8727a482328fc97157cd8d0b307d26cbb","first_computed_at":"2026-07-05T11:59:21.566027Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:59:21.566027Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"sFaRMJG/l1B9D+f526POxtVFsvHpsVoqA3K04F0icTzpc3ubJor0vWe33EffEZZsOS9n36Uuo0I07r1xQN9AAA==","signature_status":"signed_v1","signed_at":"2026-07-05T11:59:21.566505Z","signed_message":"canonical_sha256_bytes"},"source_id":"2508.17867","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:26f6e109033539a7bbaa49aa120c787caa2b47c306dff5983c4c9b3ee6ab6674","sha256:0dcadb96e50ba456c03448e39541a08e33a5a42b0142afe60540ceb8ebbd5bd4"],"state_sha256":"c240b6b63d5240bdf1b2b7e13ad71859786d8cac7705ae5c2805a5afe16ede6e"}