{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2023:HL7HSY5OCSQXE3O2OJHZ6AZIJF","short_pith_number":"pith:HL7HSY5O","schema_version":"1.0","canonical_sha256":"3afe7963ae14a1726dda724f9f03284952823c34ab25ee43216c90e4333e1859","source":{"kind":"arxiv","id":"2308.00487","version":1},"attestation_state":"computed","paper":{"title":"Data quality challenges in existing distribution network datasets","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","headline":"","cross_cats":["cs.SY"],"primary_cat":"eess.SY","authors_text":"Dirk Van Hertem, Frederik Geth, Marta Vanin","submitted_at":"2023-08-01T12:19:03Z","abstract_excerpt":"Existing digital distribution network models, like those in the databases of network utilities, are known to contain erroneous or untrustworthy information. This can compromise the effectiveness of physics-based engineering simulations and technologies, in particular those that are needed to deliver the energy transition. The large-scale rollout of smart meters presents new opportunities for data-driven system identification in distribution networks, enabling the improvement of existing data sets. Despite the increasing academic attention to system identification for distribution networks, res"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2308.00487","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"eess.SY","submitted_at":"2023-08-01T12:19:03Z","cross_cats_sorted":["cs.SY"],"title_canon_sha256":"1b5f768cab6f7938f10dca39c41c1542e15966d402f4a680f1a3a0a73277a4dd","abstract_canon_sha256":"4679cfb9146ea307bf4000111b9a8d3e0a1b0719882bef23aa1c9fda735c25c4"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T06:36:48.160438Z","signature_b64":"yYF87nfVL+nr7Nw7ntYYcXdUgBxa22QrXavFwXszmF1IOK1tPJkv/jW1bo079zxmSwIfohgqFA2w8o7JQlspDQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"3afe7963ae14a1726dda724f9f03284952823c34ab25ee43216c90e4333e1859","last_reissued_at":"2026-07-05T06:36:48.160108Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T06:36:48.160108Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Data quality challenges in existing distribution network datasets","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","headline":"","cross_cats":["cs.SY"],"primary_cat":"eess.SY","authors_text":"Dirk Van Hertem, Frederik Geth, Marta Vanin","submitted_at":"2023-08-01T12:19:03Z","abstract_excerpt":"Existing digital distribution network models, like those in the databases of network utilities, are known to contain erroneous or untrustworthy information. This can compromise the effectiveness of physics-based engineering simulations and technologies, in particular those that are needed to deliver the energy transition. The large-scale rollout of smart meters presents new opportunities for data-driven system identification in distribution networks, enabling the improvement of existing data sets. Despite the increasing academic attention to system identification for distribution networks, res"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2308.00487","kind":"arxiv","version":1},"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/2308.00487/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"},"aliases":[{"alias_kind":"arxiv","alias_value":"2308.00487","created_at":"2026-07-05T06:36:48.160158+00:00"},{"alias_kind":"arxiv_version","alias_value":"2308.00487v1","created_at":"2026-07-05T06:36:48.160158+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2308.00487","created_at":"2026-07-05T06:36:48.160158+00:00"},{"alias_kind":"pith_short_12","alias_value":"HL7HSY5OCSQX","created_at":"2026-07-05T06:36:48.160158+00:00"},{"alias_kind":"pith_short_16","alias_value":"HL7HSY5OCSQXE3O2","created_at":"2026-07-05T06:36:48.160158+00:00"},{"alias_kind":"pith_short_8","alias_value":"HL7HSY5O","created_at":"2026-07-05T06:36:48.160158+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/HL7HSY5OCSQXE3O2OJHZ6AZIJF","json":"https://pith.science/pith/HL7HSY5OCSQXE3O2OJHZ6AZIJF.json","graph_json":"https://pith.science/api/pith-number/HL7HSY5OCSQXE3O2OJHZ6AZIJF/graph.json","events_json":"https://pith.science/api/pith-number/HL7HSY5OCSQXE3O2OJHZ6AZIJF/events.json","paper":"https://pith.science/paper/HL7HSY5O"},"agent_actions":{"view_html":"https://pith.science/pith/HL7HSY5OCSQXE3O2OJHZ6AZIJF","download_json":"https://pith.science/pith/HL7HSY5OCSQXE3O2OJHZ6AZIJF.json","view_paper":"https://pith.science/paper/HL7HSY5O","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2308.00487&json=true","fetch_graph":"https://pith.science/api/pith-number/HL7HSY5OCSQXE3O2OJHZ6AZIJF/graph.json","fetch_events":"https://pith.science/api/pith-number/HL7HSY5OCSQXE3O2OJHZ6AZIJF/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/HL7HSY5OCSQXE3O2OJHZ6AZIJF/action/timestamp_anchor","attest_storage":"https://pith.science/pith/HL7HSY5OCSQXE3O2OJHZ6AZIJF/action/storage_attestation","attest_author":"https://pith.science/pith/HL7HSY5OCSQXE3O2OJHZ6AZIJF/action/author_attestation","sign_citation":"https://pith.science/pith/HL7HSY5OCSQXE3O2OJHZ6AZIJF/action/citation_signature","submit_replication":"https://pith.science/pith/HL7HSY5OCSQXE3O2OJHZ6AZIJF/action/replication_record"}},"created_at":"2026-07-05T06:36:48.160158+00:00","updated_at":"2026-07-05T06:36:48.160158+00:00"}