{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:26YZJHXEXX24EFRKU5ECKBCIVX","short_pith_number":"pith:26YZJHXE","canonical_record":{"source":{"id":"2605.13000","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"hep-ph","submitted_at":"2026-05-13T04:56:42Z","cross_cats_sorted":[],"title_canon_sha256":"6efa7df410e8dcfc0ad713e1840865456013468d43c9b679e997605c26a4fe68","abstract_canon_sha256":"75436de947cc073b9ecb514bc2a81d4f60c456bb677988b6dafea7246152bab8"},"schema_version":"1.0"},"canonical_sha256":"d7b1949ee4bdf5c2162aa748250448adf30f69819d4a0856fa35fddea82c9bfd","source":{"kind":"arxiv","id":"2605.13000","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2605.13000","created_at":"2026-05-18T03:09:00Z"},{"alias_kind":"arxiv_version","alias_value":"2605.13000v1","created_at":"2026-05-18T03:09:00Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2605.13000","created_at":"2026-05-18T03:09:00Z"},{"alias_kind":"pith_short_12","alias_value":"26YZJHXEXX24","created_at":"2026-05-18T12:33:37Z"},{"alias_kind":"pith_short_16","alias_value":"26YZJHXEXX24EFRK","created_at":"2026-05-18T12:33:37Z"},{"alias_kind":"pith_short_8","alias_value":"26YZJHXE","created_at":"2026-05-18T12:33:37Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:26YZJHXEXX24EFRKU5ECKBCIVX","target":"record","payload":{"canonical_record":{"source":{"id":"2605.13000","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"hep-ph","submitted_at":"2026-05-13T04:56:42Z","cross_cats_sorted":[],"title_canon_sha256":"6efa7df410e8dcfc0ad713e1840865456013468d43c9b679e997605c26a4fe68","abstract_canon_sha256":"75436de947cc073b9ecb514bc2a81d4f60c456bb677988b6dafea7246152bab8"},"schema_version":"1.0"},"canonical_sha256":"d7b1949ee4bdf5c2162aa748250448adf30f69819d4a0856fa35fddea82c9bfd","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T03:09:00.436243Z","signature_b64":"4Hk5vr+BVgQ/yaVQq7x4Y/MSNAeREdTg5Lt5KSvIXtScCD5Q715BTgCwXn4dKC25iLAiMrh+ZNvzqHpd3TlYDg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"d7b1949ee4bdf5c2162aa748250448adf30f69819d4a0856fa35fddea82c9bfd","last_reissued_at":"2026-05-18T03:09:00.435772Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T03:09:00.435772Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2605.13000","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T03:09:00Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"qW2BhLuXmK7KwHcrxwBS2i7MNs8ocrOpGNk97fU+rNHLRxzqNc1+NnBW6mfA6P63+QIuSERmLMgwRj56vD5bCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-26T21:24:22.386826Z"},"content_sha256":"2c7b4a98f0278c1ce2c8c2f10aa9e1428493cb5b0d9ae57c56be9a8ae5c9449f","schema_version":"1.0","event_id":"sha256:2c7b4a98f0278c1ce2c8c2f10aa9e1428493cb5b0d9ae57c56be9a8ae5c9449f"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:26YZJHXEXX24EFRKU5ECKBCIVX","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Neural Network Generalized Parton Distributions (NNGPD)","license":"http://creativecommons.org/licenses/by/4.0/","headline":"Neural networks can reconstruct generalized parton distributions by training on both experimental data and lattice QCD results.","cross_cats":[],"primary_cat":"hep-ph","authors_text":"Simonetta Liuti, Zaki Panjsheeri","submitted_at":"2026-05-13T04:56:42Z","abstract_excerpt":"Generalized parton distributions (GPDs) serve as indispensable tools for the exploration of proton structure. In this study, we offer a deep learning-assisted framework for the extraction of GPDs from experimental data and the results of ab-initio lattice quantum chromodynamics (LQCD)."},"claims":{"count":4,"items":[{"kind":"strongest_claim","text":"In this study, we offer a deep learning-assisted framework for the extraction of GPDs from experimental data and the results of ab-initio lattice quantum chromodynamics (LQCD).","source":"verdict.strongest_claim","status":"machine_extracted","claim_id":"C1","attestation":"unclaimed"},{"kind":"weakest_assumption","text":"That a neural network trained on available data and LQCD results can accurately and unbiasedly reconstruct the full GPD functions without overfitting or missing important physical constraints.","source":"verdict.weakest_assumption","status":"machine_extracted","claim_id":"C2","attestation":"unclaimed"},{"kind":"one_line_summary","text":"A deep learning-assisted framework extracts generalized parton distributions from experimental data and ab-initio lattice QCD results.","source":"verdict.one_line_summary","status":"machine_extracted","claim_id":"C3","attestation":"unclaimed"},{"kind":"headline","text":"Neural networks can reconstruct generalized parton distributions by training on both experimental data and lattice QCD results.","source":"verdict.pith_extraction.headline","status":"machine_extracted","claim_id":"C4","attestation":"unclaimed"}],"snapshot_sha256":"1f8723969749cadb2b21c8b511b407da44d7887471f10783b607d7a99b546431"},"source":{"id":"2605.13000","kind":"arxiv","version":1},"verdict":{"id":"978e4257-de0e-4e0d-a220-1941826c2268","model_set":{"reader":"grok-4.3"},"created_at":"2026-05-14T18:54:58.409310Z","strongest_claim":"In this study, we offer a deep learning-assisted framework for the extraction of GPDs from experimental data and the results of ab-initio lattice quantum chromodynamics (LQCD).","one_line_summary":"A deep learning-assisted framework extracts generalized parton distributions from experimental data and ab-initio lattice QCD results.","pipeline_version":"pith-pipeline@v0.9.0","weakest_assumption":"That a neural network trained on available data and LQCD results can accurately and unbiasedly reconstruct the full GPD functions without overfitting or missing important physical constraints.","pith_extraction_headline":"Neural networks can reconstruct generalized parton distributions by training on both experimental data and lattice QCD results."},"references":{"count":15,"sample":[{"doi":"","year":2025,"title":"AI for nuclear physics: the EXCLAIM project.JINST, 20(08):C08011, 2025","work_id":"74bf365d-04ee-48ce-80c5-9728686437a0","ref_index":1,"cited_arxiv_id":"","is_internal_anchor":false},{"doi":"","year":1997,"title":"Gauge-InvariantDecompositionofNucleonSpin.Phys","work_id":"356172a3-98f5-4289-ba32-8668c83ec563","ref_index":2,"cited_arxiv_id":"","is_internal_anchor":false},{"doi":"","year":1997,"title":"A. V. Radyushkin. Nonforward parton distributions.Phys. Rev. D, 56:5524–5557, 1997","work_id":"728e85bb-5ab5-4f37-a43e-27852d649529","ref_index":3,"cited_arxiv_id":"","is_internal_anchor":false},{"doi":"","year":1990,"title":"R. L. Jaffe and Aneesh Manohar. The𝑔1 Problem: Fact and Fantasy on the Spin of the Proton.Nucl. Phys. B, 337:509–546, 1990","work_id":"ffd06c78-751e-483d-8f25-aa6d964c1f11","ref_index":4,"cited_arxiv_id":"","is_internal_anchor":false},{"doi":"","year":2025,"title":"Generalized Parton Distributions from Symbolic Regression","work_id":"6bc583a1-c434-4ff0-b571-bb89c46daf84","ref_index":5,"cited_arxiv_id":"","is_internal_anchor":false}],"resolved_work":15,"snapshot_sha256":"585b497493b7ef12e79e892ff9fd0502f31f2eae33e308542ebd018e8349c274","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":"978e4257-de0e-4e0d-a220-1941826c2268"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T03:09:00Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"hLsf6x/kUG2S9FMwhIFCOf17qKFIVcn49zm+zrVyxMxf6ujEazL5zNt64SuUi5qQ6UC3Qcmd6CTDvp/6JZHEBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-26T21:24:22.388020Z"},"content_sha256":"3b956eaccf8120c694e5007d37af695fc88cd6beba0ba0e5ff140a7ae78312c0","schema_version":"1.0","event_id":"sha256:3b956eaccf8120c694e5007d37af695fc88cd6beba0ba0e5ff140a7ae78312c0"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/26YZJHXEXX24EFRKU5ECKBCIVX/bundle.json","state_url":"https://pith.science/pith/26YZJHXEXX24EFRKU5ECKBCIVX/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/26YZJHXEXX24EFRKU5ECKBCIVX/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":"2026-05-26T21:24:22Z","links":{"resolver":"https://pith.science/pith/26YZJHXEXX24EFRKU5ECKBCIVX","bundle":"https://pith.science/pith/26YZJHXEXX24EFRKU5ECKBCIVX/bundle.json","state":"https://pith.science/pith/26YZJHXEXX24EFRKU5ECKBCIVX/state.json","well_known_bundle":"https://pith.science/.well-known/pith/26YZJHXEXX24EFRKU5ECKBCIVX/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:26YZJHXEXX24EFRKU5ECKBCIVX","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":"75436de947cc073b9ecb514bc2a81d4f60c456bb677988b6dafea7246152bab8","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"hep-ph","submitted_at":"2026-05-13T04:56:42Z","title_canon_sha256":"6efa7df410e8dcfc0ad713e1840865456013468d43c9b679e997605c26a4fe68"},"schema_version":"1.0","source":{"id":"2605.13000","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2605.13000","created_at":"2026-05-18T03:09:00Z"},{"alias_kind":"arxiv_version","alias_value":"2605.13000v1","created_at":"2026-05-18T03:09:00Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2605.13000","created_at":"2026-05-18T03:09:00Z"},{"alias_kind":"pith_short_12","alias_value":"26YZJHXEXX24","created_at":"2026-05-18T12:33:37Z"},{"alias_kind":"pith_short_16","alias_value":"26YZJHXEXX24EFRK","created_at":"2026-05-18T12:33:37Z"},{"alias_kind":"pith_short_8","alias_value":"26YZJHXE","created_at":"2026-05-18T12:33:37Z"}],"graph_snapshots":[{"event_id":"sha256:3b956eaccf8120c694e5007d37af695fc88cd6beba0ba0e5ff140a7ae78312c0","target":"graph","created_at":"2026-05-18T03:09:00Z","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":4,"items":[{"attestation":"unclaimed","claim_id":"C1","kind":"strongest_claim","source":"verdict.strongest_claim","status":"machine_extracted","text":"In this study, we offer a deep learning-assisted framework for the extraction of GPDs from experimental data and the results of ab-initio lattice quantum chromodynamics (LQCD)."},{"attestation":"unclaimed","claim_id":"C2","kind":"weakest_assumption","source":"verdict.weakest_assumption","status":"machine_extracted","text":"That a neural network trained on available data and LQCD results can accurately and unbiasedly reconstruct the full GPD functions without overfitting or missing important physical constraints."},{"attestation":"unclaimed","claim_id":"C3","kind":"one_line_summary","source":"verdict.one_line_summary","status":"machine_extracted","text":"A deep learning-assisted framework extracts generalized parton distributions from experimental data and ab-initio lattice QCD results."},{"attestation":"unclaimed","claim_id":"C4","kind":"headline","source":"verdict.pith_extraction.headline","status":"machine_extracted","text":"Neural networks can reconstruct generalized parton distributions by training on both experimental data and lattice QCD results."}],"snapshot_sha256":"1f8723969749cadb2b21c8b511b407da44d7887471f10783b607d7a99b546431"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"paper":{"abstract_excerpt":"Generalized parton distributions (GPDs) serve as indispensable tools for the exploration of proton structure. In this study, we offer a deep learning-assisted framework for the extraction of GPDs from experimental data and the results of ab-initio lattice quantum chromodynamics (LQCD).","authors_text":"Simonetta Liuti, Zaki Panjsheeri","cross_cats":[],"headline":"Neural networks can reconstruct generalized parton distributions by training on both experimental data and lattice QCD results.","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"hep-ph","submitted_at":"2026-05-13T04:56:42Z","title":"Neural Network Generalized Parton Distributions (NNGPD)"},"references":{"count":15,"internal_anchors":0,"resolved_work":15,"sample":[{"cited_arxiv_id":"","doi":"","is_internal_anchor":false,"ref_index":1,"title":"AI for nuclear physics: the EXCLAIM project.JINST, 20(08):C08011, 2025","work_id":"74bf365d-04ee-48ce-80c5-9728686437a0","year":2025},{"cited_arxiv_id":"","doi":"","is_internal_anchor":false,"ref_index":2,"title":"Gauge-InvariantDecompositionofNucleonSpin.Phys","work_id":"356172a3-98f5-4289-ba32-8668c83ec563","year":1997},{"cited_arxiv_id":"","doi":"","is_internal_anchor":false,"ref_index":3,"title":"A. V. Radyushkin. Nonforward parton distributions.Phys. Rev. D, 56:5524–5557, 1997","work_id":"728e85bb-5ab5-4f37-a43e-27852d649529","year":1997},{"cited_arxiv_id":"","doi":"","is_internal_anchor":false,"ref_index":4,"title":"R. L. Jaffe and Aneesh Manohar. The𝑔1 Problem: Fact and Fantasy on the Spin of the Proton.Nucl. Phys. B, 337:509–546, 1990","work_id":"ffd06c78-751e-483d-8f25-aa6d964c1f11","year":1990},{"cited_arxiv_id":"","doi":"","is_internal_anchor":false,"ref_index":5,"title":"Generalized Parton Distributions from Symbolic Regression","work_id":"6bc583a1-c434-4ff0-b571-bb89c46daf84","year":2025}],"snapshot_sha256":"585b497493b7ef12e79e892ff9fd0502f31f2eae33e308542ebd018e8349c274"},"source":{"id":"2605.13000","kind":"arxiv","version":1},"verdict":{"created_at":"2026-05-14T18:54:58.409310Z","id":"978e4257-de0e-4e0d-a220-1941826c2268","model_set":{"reader":"grok-4.3"},"one_line_summary":"A deep learning-assisted framework extracts generalized parton distributions from experimental data and ab-initio lattice QCD results.","pipeline_version":"pith-pipeline@v0.9.0","pith_extraction_headline":"Neural networks can reconstruct generalized parton distributions by training on both experimental data and lattice QCD results.","strongest_claim":"In this study, we offer a deep learning-assisted framework for the extraction of GPDs from experimental data and the results of ab-initio lattice quantum chromodynamics (LQCD).","weakest_assumption":"That a neural network trained on available data and LQCD results can accurately and unbiasedly reconstruct the full GPD functions without overfitting or missing important physical constraints."}},"verdict_id":"978e4257-de0e-4e0d-a220-1941826c2268"}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:2c7b4a98f0278c1ce2c8c2f10aa9e1428493cb5b0d9ae57c56be9a8ae5c9449f","target":"record","created_at":"2026-05-18T03:09:00Z","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":"75436de947cc073b9ecb514bc2a81d4f60c456bb677988b6dafea7246152bab8","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"hep-ph","submitted_at":"2026-05-13T04:56:42Z","title_canon_sha256":"6efa7df410e8dcfc0ad713e1840865456013468d43c9b679e997605c26a4fe68"},"schema_version":"1.0","source":{"id":"2605.13000","kind":"arxiv","version":1}},"canonical_sha256":"d7b1949ee4bdf5c2162aa748250448adf30f69819d4a0856fa35fddea82c9bfd","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"d7b1949ee4bdf5c2162aa748250448adf30f69819d4a0856fa35fddea82c9bfd","first_computed_at":"2026-05-18T03:09:00.435772Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T03:09:00.435772Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"4Hk5vr+BVgQ/yaVQq7x4Y/MSNAeREdTg5Lt5KSvIXtScCD5Q715BTgCwXn4dKC25iLAiMrh+ZNvzqHpd3TlYDg==","signature_status":"signed_v1","signed_at":"2026-05-18T03:09:00.436243Z","signed_message":"canonical_sha256_bytes"},"source_id":"2605.13000","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:2c7b4a98f0278c1ce2c8c2f10aa9e1428493cb5b0d9ae57c56be9a8ae5c9449f","sha256:3b956eaccf8120c694e5007d37af695fc88cd6beba0ba0e5ff140a7ae78312c0"],"state_sha256":"dcbc8d068d2f5e3ab3af8ff89e023906cfd79bbdc9211fe82186fe0c9fc40df0"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"DAhEgLFeyPfbDg+WGBi/83FeRSRoGICnNmZx60tR4c+T69JMD+LhNC5pIlwSGf9suUi8OSJ3JYwodjkSxnCzCw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-26T21:24:22.392804Z","bundle_sha256":"f988467052dbe29aacdc32fc315808926ba69e781534d9115243b5609a07b69e"}}