{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:PRIUVX3VBQDCY3CD77C3GER6RD","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":"5637361857ee36cb1d22cd2dd2ca9c3f08ebe49bf7ec6b14410754d26c1640bf","cross_cats_sorted":["econ.GN","q-fin.EC"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CY","submitted_at":"2025-03-12T01:19:52Z","title_canon_sha256":"5bcc8145971910b11a4ad9d6634e146fad9eb080354c07b27d50d63344ec06f5"},"schema_version":"1.0","source":{"id":"2503.09637","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2503.09637","created_at":"2026-07-05T12:04:14Z"},{"alias_kind":"arxiv_version","alias_value":"2503.09637v1","created_at":"2026-07-05T12:04:14Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2503.09637","created_at":"2026-07-05T12:04:14Z"},{"alias_kind":"pith_short_12","alias_value":"PRIUVX3VBQDC","created_at":"2026-07-05T12:04:14Z"},{"alias_kind":"pith_short_16","alias_value":"PRIUVX3VBQDCY3CD","created_at":"2026-07-05T12:04:14Z"},{"alias_kind":"pith_short_8","alias_value":"PRIUVX3V","created_at":"2026-07-05T12:04:14Z"}],"graph_snapshots":[{"event_id":"sha256:b49301c201b5646263f79cd7ea6647729b1a78ad749c2df8c0dc7ea4359b19a2","target":"graph","created_at":"2026-07-05T12:04:14Z","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/2503.09637/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"This study investigates the near-future impacts of generative artificial intelligence (AI) technologies on occupational competencies across the U.S. federal workforce. We develop a multi-stage Retrieval-Augmented Generation system to leverage large language models for predictive AI modeling that projects shifts in required competencies and to identify vulnerable occupations on a knowledge-by-skill-by-ability basis across the federal government workforce. This study highlights policy recommendations essential for workforce planning in the era of AI. We integrate several sources of detailed data","authors_text":"Brandon De Bruhl, Gul Nisa G\\\"urb\\\"uz, Michael Overton, William G. Resh, Xinyao Xia, Yi Ming","cross_cats":["econ.GN","q-fin.EC"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CY","submitted_at":"2025-03-12T01:19:52Z","title":"Complementarity, Augmentation, or Substitutivity? The Impact of Generative Artificial Intelligence on the U.S. Federal Workforce"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2503.09637","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":"sha256:0bc7e0b39d65a94338fbe39abf2f52be83e19b82b517d9c9688e0a6af8db847f","target":"record","created_at":"2026-07-05T12:04:14Z","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":"5637361857ee36cb1d22cd2dd2ca9c3f08ebe49bf7ec6b14410754d26c1640bf","cross_cats_sorted":["econ.GN","q-fin.EC"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CY","submitted_at":"2025-03-12T01:19:52Z","title_canon_sha256":"5bcc8145971910b11a4ad9d6634e146fad9eb080354c07b27d50d63344ec06f5"},"schema_version":"1.0","source":{"id":"2503.09637","kind":"arxiv","version":1}},"canonical_sha256":"7c514adf750c062c6c43ffc5b3123e88d95d9f8b1cd7df0d37b18b19f55c5726","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"7c514adf750c062c6c43ffc5b3123e88d95d9f8b1cd7df0d37b18b19f55c5726","first_computed_at":"2026-07-05T12:04:14.193806Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T12:04:14.193806Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"LchmlucB43fNLH9O2e0K6Lm7GQHFZ0jTxMaoZMhkRdckWjHFnAsJfs/oJ1SFqZFGDyX7Vfm9Pu7KwqJHto/ZCg==","signature_status":"signed_v1","signed_at":"2026-07-05T12:04:14.194330Z","signed_message":"canonical_sha256_bytes"},"source_id":"2503.09637","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:0bc7e0b39d65a94338fbe39abf2f52be83e19b82b517d9c9688e0a6af8db847f","sha256:b49301c201b5646263f79cd7ea6647729b1a78ad749c2df8c0dc7ea4359b19a2"],"state_sha256":"64c5ad1e3fe79e5fab79439b6d1abc135856f8487f91de22ec03e8e8774b491e"}