{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2023:SGV7AFS5SSWFGKOWCGRLOKZ6BC","short_pith_number":"pith:SGV7AFS5","schema_version":"1.0","canonical_sha256":"91abf0165d94ac5329d611a2b72b3e08b197b9b72e4261c8a08b43f1c102e603","source":{"kind":"arxiv","id":"2301.07210","version":4},"attestation_state":"computed","paper":{"title":"Causal Falsification of Digital Twins","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.CE","cs.LG","stat.AP"],"primary_cat":"stat.ME","authors_text":"Arnaud Doucet, Chris Holmes, Muhammad Faaiz Taufiq, Rob Cornish","submitted_at":"2023-01-17T22:18:53Z","abstract_excerpt":"Digital twins are virtual systems designed to predict how a real-world process will evolve in response to interventions. This modelling paradigm holds substantial promise in many applications, but rigorous procedures for assessing their accuracy are essential for safety-critical settings. We consider how to assess the accuracy of a digital twin using real-world data. We formulate this as causal inference problem, which leads to a precise definition of what it means for a twin to be \"correct\" appropriate for many applications. Unfortunately, fundamental results from causal inference mean observ"},"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":"2301.07210","kind":"arxiv","version":4},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"stat.ME","submitted_at":"2023-01-17T22:18:53Z","cross_cats_sorted":["cs.CE","cs.LG","stat.AP"],"title_canon_sha256":"e398a7f586a58bf1e4a9066ebfc5da96a7d51cbf88d1fd27c08711555baf788b","abstract_canon_sha256":"81da14ad0965e895bf1a5cbc545e220d621dfe21cb52a7f4c1d9197eb7dafe85"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T07:08:04.786159Z","signature_b64":"4Acw/NMzNjBNcwdIJKkBCkNymTy2vz3cw2N+3J8fcZXv+dKEITSvosmWm6sXND+ZEG29nIOu2S4Ne26KFUJNDw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"91abf0165d94ac5329d611a2b72b3e08b197b9b72e4261c8a08b43f1c102e603","last_reissued_at":"2026-07-05T07:08:04.785808Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T07:08:04.785808Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Causal Falsification of Digital Twins","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.CE","cs.LG","stat.AP"],"primary_cat":"stat.ME","authors_text":"Arnaud Doucet, Chris Holmes, Muhammad Faaiz Taufiq, Rob Cornish","submitted_at":"2023-01-17T22:18:53Z","abstract_excerpt":"Digital twins are virtual systems designed to predict how a real-world process will evolve in response to interventions. This modelling paradigm holds substantial promise in many applications, but rigorous procedures for assessing their accuracy are essential for safety-critical settings. We consider how to assess the accuracy of a digital twin using real-world data. We formulate this as causal inference problem, which leads to a precise definition of what it means for a twin to be \"correct\" appropriate for many applications. Unfortunately, fundamental results from causal inference mean observ"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2301.07210","kind":"arxiv","version":4},"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/2301.07210/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":"2301.07210","created_at":"2026-07-05T07:08:04.785865+00:00"},{"alias_kind":"arxiv_version","alias_value":"2301.07210v4","created_at":"2026-07-05T07:08:04.785865+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2301.07210","created_at":"2026-07-05T07:08:04.785865+00:00"},{"alias_kind":"pith_short_12","alias_value":"SGV7AFS5SSWF","created_at":"2026-07-05T07:08:04.785865+00:00"},{"alias_kind":"pith_short_16","alias_value":"SGV7AFS5SSWFGKOW","created_at":"2026-07-05T07:08:04.785865+00:00"},{"alias_kind":"pith_short_8","alias_value":"SGV7AFS5","created_at":"2026-07-05T07:08:04.785865+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/SGV7AFS5SSWFGKOWCGRLOKZ6BC","json":"https://pith.science/pith/SGV7AFS5SSWFGKOWCGRLOKZ6BC.json","graph_json":"https://pith.science/api/pith-number/SGV7AFS5SSWFGKOWCGRLOKZ6BC/graph.json","events_json":"https://pith.science/api/pith-number/SGV7AFS5SSWFGKOWCGRLOKZ6BC/events.json","paper":"https://pith.science/paper/SGV7AFS5"},"agent_actions":{"view_html":"https://pith.science/pith/SGV7AFS5SSWFGKOWCGRLOKZ6BC","download_json":"https://pith.science/pith/SGV7AFS5SSWFGKOWCGRLOKZ6BC.json","view_paper":"https://pith.science/paper/SGV7AFS5","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2301.07210&json=true","fetch_graph":"https://pith.science/api/pith-number/SGV7AFS5SSWFGKOWCGRLOKZ6BC/graph.json","fetch_events":"https://pith.science/api/pith-number/SGV7AFS5SSWFGKOWCGRLOKZ6BC/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/SGV7AFS5SSWFGKOWCGRLOKZ6BC/action/timestamp_anchor","attest_storage":"https://pith.science/pith/SGV7AFS5SSWFGKOWCGRLOKZ6BC/action/storage_attestation","attest_author":"https://pith.science/pith/SGV7AFS5SSWFGKOWCGRLOKZ6BC/action/author_attestation","sign_citation":"https://pith.science/pith/SGV7AFS5SSWFGKOWCGRLOKZ6BC/action/citation_signature","submit_replication":"https://pith.science/pith/SGV7AFS5SSWFGKOWCGRLOKZ6BC/action/replication_record"}},"created_at":"2026-07-05T07:08:04.785865+00:00","updated_at":"2026-07-05T07:08:04.785865+00:00"}