{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:LF74R3JV3LYDFC3L3RFOENF4RG","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":"8b9154e0c8ab5d818864b018e48362dc2a7330f96f9828032c03a3b35acb6f93","cross_cats_sorted":["cs.AI","cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.IV","submitted_at":"2025-02-10T16:24:18Z","title_canon_sha256":"f9e961e3ea9bc873c7b9c1e6fb75ff2d0cf50967db9a10c32b1fa57fed06a1d2"},"schema_version":"1.0","source":{"id":"2502.06920","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2502.06920","created_at":"2026-07-05T10:12:30Z"},{"alias_kind":"arxiv_version","alias_value":"2502.06920v1","created_at":"2026-07-05T10:12:30Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2502.06920","created_at":"2026-07-05T10:12:30Z"},{"alias_kind":"pith_short_12","alias_value":"LF74R3JV3LYD","created_at":"2026-07-05T10:12:30Z"},{"alias_kind":"pith_short_16","alias_value":"LF74R3JV3LYDFC3L","created_at":"2026-07-05T10:12:30Z"},{"alias_kind":"pith_short_8","alias_value":"LF74R3JV","created_at":"2026-07-05T10:12:30Z"}],"graph_snapshots":[{"event_id":"sha256:05fd9b145f829992551082f2cd8a9c31ebc3c2ad4212c0caf37017c3e02dccc9","target":"graph","created_at":"2026-07-05T10:12:30Z","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/2502.06920/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"In many pediatric fMRI studies, cardiac signals are often missing or of poor quality. A tool to extract Heart Rate Variation (HRV) waveforms directly from fMRI data, without the need for peripheral recording devices, would be highly beneficial. We developed a machine learning framework to accurately reconstruct HRV for pediatric applications. A hybrid model combining one-dimensional Convolutional Neural Networks (1D-CNN) and Gated Recurrent Units (GRU) analyzed BOLD signals from 628 ROIs, integrating past and future data. The model achieved an 8% improvement in HRV accuracy, as evidenced by en","authors_text":"Abdoljalil Addeh, G. Bruce Pike, Karen Ardila, M. Ethan MacDonald, Rebecca J Williams","cross_cats":["cs.AI","cs.LG"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.IV","submitted_at":"2025-02-10T16:24:18Z","title":"Direct Estimation of Pediatric Heart Rate Variability from BOLD-fMRI: A Machine Learning Approach Using Dynamic Connectivity"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2502.06920","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":"sha256:9ab375bfa2ea0dc3ffe694c3886b66bd9cac8cbba11580e2ad91ffff8232ff33","target":"record","created_at":"2026-07-05T10:12:30Z","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":"8b9154e0c8ab5d818864b018e48362dc2a7330f96f9828032c03a3b35acb6f93","cross_cats_sorted":["cs.AI","cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.IV","submitted_at":"2025-02-10T16:24:18Z","title_canon_sha256":"f9e961e3ea9bc873c7b9c1e6fb75ff2d0cf50967db9a10c32b1fa57fed06a1d2"},"schema_version":"1.0","source":{"id":"2502.06920","kind":"arxiv","version":1}},"canonical_sha256":"597fc8ed35daf0328b6bdc4ae234bc89ae69a646dfbeb12f30f96d9ca14d783c","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"597fc8ed35daf0328b6bdc4ae234bc89ae69a646dfbeb12f30f96d9ca14d783c","first_computed_at":"2026-07-05T10:12:30.327726Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:12:30.327726Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"FXRekIvOH9S23H450lpTq3GJ1A4wo1VMwGanZ9+PBPgcAqQFn5K4WA/HlM6pDsNQ4MmGrzAy+z7vODKNYnkVDw==","signature_status":"signed_v1","signed_at":"2026-07-05T10:12:30.328270Z","signed_message":"canonical_sha256_bytes"},"source_id":"2502.06920","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:9ab375bfa2ea0dc3ffe694c3886b66bd9cac8cbba11580e2ad91ffff8232ff33","sha256:05fd9b145f829992551082f2cd8a9c31ebc3c2ad4212c0caf37017c3e02dccc9"],"state_sha256":"177b5f5bc93b1d2317148f9aad1e63e058669aa4a2a676c325dfa8033102a1a6"}