{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:NVUGLWKFLXV2L3X4YF6OLP6OFI","short_pith_number":"pith:NVUGLWKF","canonical_record":{"source":{"id":"2504.13289","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"hep-ph","submitted_at":"2025-04-17T18:59:47Z","cross_cats_sorted":["hep-lat"],"title_canon_sha256":"6a9872d9afef2a1e473bb7b992f78e00e15e95e0c6a05cfd9981e958713af4a3","abstract_canon_sha256":"5468b76b3b5e20cc2db3b272619f6e8189a317d0cb188718b6c969db67550dda"},"schema_version":"1.0"},"canonical_sha256":"6d6865d9455deba5eefcc17ce5bfce2a36006aaf5a44900c75f80bb4a5d2b4d8","source":{"kind":"arxiv","id":"2504.13289","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2504.13289","created_at":"2026-07-05T11:30:43Z"},{"alias_kind":"arxiv_version","alias_value":"2504.13289v3","created_at":"2026-07-05T11:30:43Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2504.13289","created_at":"2026-07-05T11:30:43Z"},{"alias_kind":"pith_short_12","alias_value":"NVUGLWKFLXV2","created_at":"2026-07-05T11:30:43Z"},{"alias_kind":"pith_short_16","alias_value":"NVUGLWKFLXV2L3X4","created_at":"2026-07-05T11:30:43Z"},{"alias_kind":"pith_short_8","alias_value":"NVUGLWKF","created_at":"2026-07-05T11:30:43Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:NVUGLWKFLXV2L3X4YF6OLP6OFI","target":"record","payload":{"canonical_record":{"source":{"id":"2504.13289","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"hep-ph","submitted_at":"2025-04-17T18:59:47Z","cross_cats_sorted":["hep-lat"],"title_canon_sha256":"6a9872d9afef2a1e473bb7b992f78e00e15e95e0c6a05cfd9981e958713af4a3","abstract_canon_sha256":"5468b76b3b5e20cc2db3b272619f6e8189a317d0cb188718b6c969db67550dda"},"schema_version":"1.0"},"canonical_sha256":"6d6865d9455deba5eefcc17ce5bfce2a36006aaf5a44900c75f80bb4a5d2b4d8","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:30:43.363105Z","signature_b64":"NTYRBZfyelD8Jqoo4NzhwiamD/5eLRbnFlxyRg9F8KCcR6XhIS00BPFZf2h22KC3MjIc8l5NOUsrmB/bIj9oCQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"6d6865d9455deba5eefcc17ce5bfce2a36006aaf5a44900c75f80bb4a5d2b4d8","last_reissued_at":"2026-07-05T11:30:43.362584Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:30:43.362584Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2504.13289","source_version":3,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T11:30:43Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"a5LYb4mXLaC8b1Z7oAD+sstmqHYrpL+a2x8/xBC3usrGHpQhm+DsKBz9YFCA83WlRoRSn9Tpn+JzjMg17qofDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-03T19:51:49.161757Z"},"content_sha256":"8f1e0c26ed57a4d54f3c8b10fec55f81c41321e89749d311d3cf332a7b8621c4","schema_version":"1.0","event_id":"sha256:8f1e0c26ed57a4d54f3c8b10fec55f81c41321e89749d311d3cf332a7b8621c4"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:NVUGLWKFLXV2L3X4YF6OLP6OFI","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Generalized Parton Distributions from Symbolic Regression","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["hep-lat"],"primary_cat":"hep-ph","authors_text":"Andrew Dotson, Anusha Reddy Singireddy, Douglas Q. Adams, Emmanuel Ortiz-Pacheco, Gary R. Goldstein, Gia-Wei Chern, Huey-Wen Lin, Marie Boer, Marija Cuic, Matthew D. Sievert, Michael Engelhardt, Simonetta Liuti, Yaohang Li, Zaki Panjsheeri","submitted_at":"2025-04-17T18:59:47Z","abstract_excerpt":"AI/ML informed Symbolic Regression is the next stage of scientific modeling. We utilize a highly customizable symbolic regression package ``PySR\" to model the $x$ and $t$ dependence of the flavor isovector combination $H_{u-d}(x,t,\\xi)$ at $\\xi=0$. These PySR models were trained on GPD results provided by both Lattice QCD and phenomenological sources GGL, GK, and VGG. We demonstrate, for the first time, the consistency and systematic convergence of Symbolic Regression by quantifying the disparate models through their Taylor expansion coefficients. In addition to PySR penalizing models with hig"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2504.13289","kind":"arxiv","version":3},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2504.13289/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T11:30:43Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"4b3lfdJadwfww/TCUtsxGEawmb3Br2xD49TzK4AhOAAnjHajvUpRBmwAuhvi0DsFJmK8m7mmj9uy4TUsNNxIBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-03T19:51:49.162428Z"},"content_sha256":"d392eccca006fd0a0ea1c1322c5b4998dc517d28cdc48c86b522859c9a3dc781","schema_version":"1.0","event_id":"sha256:d392eccca006fd0a0ea1c1322c5b4998dc517d28cdc48c86b522859c9a3dc781"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/NVUGLWKFLXV2L3X4YF6OLP6OFI/bundle.json","state_url":"https://pith.science/pith/NVUGLWKFLXV2L3X4YF6OLP6OFI/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/NVUGLWKFLXV2L3X4YF6OLP6OFI/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-08-03T19:51:49Z","links":{"resolver":"https://pith.science/pith/NVUGLWKFLXV2L3X4YF6OLP6OFI","bundle":"https://pith.science/pith/NVUGLWKFLXV2L3X4YF6OLP6OFI/bundle.json","state":"https://pith.science/pith/NVUGLWKFLXV2L3X4YF6OLP6OFI/state.json","well_known_bundle":"https://pith.science/.well-known/pith/NVUGLWKFLXV2L3X4YF6OLP6OFI/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:NVUGLWKFLXV2L3X4YF6OLP6OFI","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":"5468b76b3b5e20cc2db3b272619f6e8189a317d0cb188718b6c969db67550dda","cross_cats_sorted":["hep-lat"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"hep-ph","submitted_at":"2025-04-17T18:59:47Z","title_canon_sha256":"6a9872d9afef2a1e473bb7b992f78e00e15e95e0c6a05cfd9981e958713af4a3"},"schema_version":"1.0","source":{"id":"2504.13289","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2504.13289","created_at":"2026-07-05T11:30:43Z"},{"alias_kind":"arxiv_version","alias_value":"2504.13289v3","created_at":"2026-07-05T11:30:43Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2504.13289","created_at":"2026-07-05T11:30:43Z"},{"alias_kind":"pith_short_12","alias_value":"NVUGLWKFLXV2","created_at":"2026-07-05T11:30:43Z"},{"alias_kind":"pith_short_16","alias_value":"NVUGLWKFLXV2L3X4","created_at":"2026-07-05T11:30:43Z"},{"alias_kind":"pith_short_8","alias_value":"NVUGLWKF","created_at":"2026-07-05T11:30:43Z"}],"graph_snapshots":[{"event_id":"sha256:d392eccca006fd0a0ea1c1322c5b4998dc517d28cdc48c86b522859c9a3dc781","target":"graph","created_at":"2026-07-05T11:30:43Z","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/2504.13289/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"AI/ML informed Symbolic Regression is the next stage of scientific modeling. We utilize a highly customizable symbolic regression package ``PySR\" to model the $x$ and $t$ dependence of the flavor isovector combination $H_{u-d}(x,t,\\xi)$ at $\\xi=0$. These PySR models were trained on GPD results provided by both Lattice QCD and phenomenological sources GGL, GK, and VGG. We demonstrate, for the first time, the consistency and systematic convergence of Symbolic Regression by quantifying the disparate models through their Taylor expansion coefficients. In addition to PySR penalizing models with hig","authors_text":"Andrew Dotson, Anusha Reddy Singireddy, Douglas Q. Adams, Emmanuel Ortiz-Pacheco, Gary R. Goldstein, Gia-Wei Chern, Huey-Wen Lin, Marie Boer, Marija Cuic, Matthew D. Sievert, Michael Engelhardt, Simonetta Liuti, Yaohang Li, Zaki Panjsheeri","cross_cats":["hep-lat"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"hep-ph","submitted_at":"2025-04-17T18:59:47Z","title":"Generalized Parton Distributions from Symbolic Regression"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2504.13289","kind":"arxiv","version":3},"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":"sha256:8f1e0c26ed57a4d54f3c8b10fec55f81c41321e89749d311d3cf332a7b8621c4","target":"record","created_at":"2026-07-05T11:30:43Z","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":"5468b76b3b5e20cc2db3b272619f6e8189a317d0cb188718b6c969db67550dda","cross_cats_sorted":["hep-lat"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"hep-ph","submitted_at":"2025-04-17T18:59:47Z","title_canon_sha256":"6a9872d9afef2a1e473bb7b992f78e00e15e95e0c6a05cfd9981e958713af4a3"},"schema_version":"1.0","source":{"id":"2504.13289","kind":"arxiv","version":3}},"canonical_sha256":"6d6865d9455deba5eefcc17ce5bfce2a36006aaf5a44900c75f80bb4a5d2b4d8","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"6d6865d9455deba5eefcc17ce5bfce2a36006aaf5a44900c75f80bb4a5d2b4d8","first_computed_at":"2026-07-05T11:30:43.362584Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:30:43.362584Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"NTYRBZfyelD8Jqoo4NzhwiamD/5eLRbnFlxyRg9F8KCcR6XhIS00BPFZf2h22KC3MjIc8l5NOUsrmB/bIj9oCQ==","signature_status":"signed_v1","signed_at":"2026-07-05T11:30:43.363105Z","signed_message":"canonical_sha256_bytes"},"source_id":"2504.13289","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:8f1e0c26ed57a4d54f3c8b10fec55f81c41321e89749d311d3cf332a7b8621c4","sha256:d392eccca006fd0a0ea1c1322c5b4998dc517d28cdc48c86b522859c9a3dc781"],"state_sha256":"47b3064995c88b97d9e24dbae3a32ec4bf8cd169915cfa4295fab309538ff86e"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"tEyXDq51q7p6bltnPPFyCSufCLU8g76mdYCZ4SGaXL4+ED/+dblxXYqWraYevrYjTCIkSFdHQs/kAjK8CzZ7DA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-03T19:51:49.165235Z","bundle_sha256":"a6775bca0971a2bc5fe483f3a3e1188a7db4a928e3e9e894afbfbe0b2622af34"}}