{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2021:EVT2P5OGAAV64Y5NIZPHJKY74P","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":"5cb7ca6dadcad15e25085152604f7a642e9d1c1e73c566a15b5824bfb1a34e5f","cross_cats_sorted":["cs.AI","cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.SP","submitted_at":"2021-04-16T20:32:10Z","title_canon_sha256":"fb8e962cbf55fe0fb2e56fc1e336a6845a0de8dda0a34aae8adf5608f9d601ac"},"schema_version":"1.0","source":{"id":"2104.08336","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2104.08336","created_at":"2026-07-05T04:04:38Z"},{"alias_kind":"arxiv_version","alias_value":"2104.08336v2","created_at":"2026-07-05T04:04:38Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2104.08336","created_at":"2026-07-05T04:04:38Z"},{"alias_kind":"pith_short_12","alias_value":"EVT2P5OGAAV6","created_at":"2026-07-05T04:04:38Z"},{"alias_kind":"pith_short_16","alias_value":"EVT2P5OGAAV64Y5N","created_at":"2026-07-05T04:04:38Z"},{"alias_kind":"pith_short_8","alias_value":"EVT2P5OG","created_at":"2026-07-05T04:04:38Z"}],"graph_snapshots":[{"event_id":"sha256:39d164a83367772ce4a56e7071e936a71fd0b0033d66654758467944af5cdb43","target":"graph","created_at":"2026-07-05T04:04:38Z","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/2104.08336/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Automated seizure detection and classification from electroencephalography (EEG) can greatly improve seizure diagnosis and treatment. However, several modeling challenges remain unaddressed in prior automated seizure detection and classification studies: (1) representing non-Euclidean data structure in EEGs, (2) accurately classifying rare seizure types, and (3) lacking a quantitative interpretability approach to measure model ability to localize seizures. In this study, we address these challenges by (1) representing the spatiotemporal dependencies in EEGs using a graph neural network (GNN) a","authors_text":"Christopher Lee-Messer, Daniel L. Rubin, Florian Dubost, Jared A. Dunnmon, Khaled Saab, Qianying Huang, Siyi Tang, Xuan Zhang","cross_cats":["cs.AI","cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.SP","submitted_at":"2021-04-16T20:32:10Z","title":"Self-Supervised Graph Neural Networks for Improved Electroencephalographic Seizure Analysis"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2104.08336","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":"sha256:461f40f06dc812d8cfc339b1ef261ca0654f88023c378719fd8ea9705f516b63","target":"record","created_at":"2026-07-05T04:04:38Z","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":"5cb7ca6dadcad15e25085152604f7a642e9d1c1e73c566a15b5824bfb1a34e5f","cross_cats_sorted":["cs.AI","cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.SP","submitted_at":"2021-04-16T20:32:10Z","title_canon_sha256":"fb8e962cbf55fe0fb2e56fc1e336a6845a0de8dda0a34aae8adf5608f9d601ac"},"schema_version":"1.0","source":{"id":"2104.08336","kind":"arxiv","version":2}},"canonical_sha256":"2567a7f5c6002bee63ad465e74ab1fe3fb3ea568fad93abf944f808f50fc5e02","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"2567a7f5c6002bee63ad465e74ab1fe3fb3ea568fad93abf944f808f50fc5e02","first_computed_at":"2026-07-05T04:04:38.678340Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T04:04:38.678340Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"GTAEIhm0i7AKyng+I5CKP459WC5465PEEI1tqF2P6x3CgnOD8LDJ/P3DOZ9Xm0qO80yh+FyLLO9p1BccSLcNAQ==","signature_status":"signed_v1","signed_at":"2026-07-05T04:04:38.678863Z","signed_message":"canonical_sha256_bytes"},"source_id":"2104.08336","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:461f40f06dc812d8cfc339b1ef261ca0654f88023c378719fd8ea9705f516b63","sha256:39d164a83367772ce4a56e7071e936a71fd0b0033d66654758467944af5cdb43"],"state_sha256":"d31a8471f1831a044f3d028a98d9b830d86881115cc273134a707250dd3de680"}