{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2018:AR6JWG5D7BXHLTW62UQVYBITUP","short_pith_number":"pith:AR6JWG5D","schema_version":"1.0","canonical_sha256":"047c9b1ba3f86e75ceded5215c0513a3f91a08974d0246aa2d2f68d24f0a6d7b","source":{"kind":"arxiv","id":"1803.03731","version":2},"attestation_state":"computed","paper":{"title":"Model Structural Inference using Local Dynamic Operators","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["math.AP"],"primary_cat":"math.DS","authors_text":"Anthony M. DeGennaro, Balasubramanya T. Nadiga, Nathan M. Urban, Terry Haut","submitted_at":"2018-03-10T00:58:42Z","abstract_excerpt":"This paper focuses on the problem of quantifying the effects of model-structure uncertainty in the context of time-evolving dynamical systems. This is motivated by multi-model uncertainty in computer physics simulations: developers often make different modeling choices in numerical approximations and process simplifications, leading to different numerical codes that ostensibly represent the same underlying dynamics. We consider model-structure inference as a two-step methodology: the first step is to perform system identification on numerical codes for which it is possible to observe the full "},"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":"1803.03731","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.DS","submitted_at":"2018-03-10T00:58:42Z","cross_cats_sorted":["math.AP"],"title_canon_sha256":"a466c89048585d3814deaf2d7b2e8383f8de7cf929f47eeec79d30985cbc2ec1","abstract_canon_sha256":"87e0d30f853982ffdbd22c1ed1f595582cb348a7b62035b080854d8a0e3b9fb0"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:55:03.569358Z","signature_b64":"k3n0gNByOYacW3WzfO3iFiBoCF/mct+hrlGHuEBPFtBgyrbLeJ9lJS2virLRlEGWA8vJpotj0uDGgrhqBz+oDA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"047c9b1ba3f86e75ceded5215c0513a3f91a08974d0246aa2d2f68d24f0a6d7b","last_reissued_at":"2026-05-17T23:55:03.568929Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:55:03.568929Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Model Structural Inference using Local Dynamic Operators","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["math.AP"],"primary_cat":"math.DS","authors_text":"Anthony M. DeGennaro, Balasubramanya T. Nadiga, Nathan M. Urban, Terry Haut","submitted_at":"2018-03-10T00:58:42Z","abstract_excerpt":"This paper focuses on the problem of quantifying the effects of model-structure uncertainty in the context of time-evolving dynamical systems. This is motivated by multi-model uncertainty in computer physics simulations: developers often make different modeling choices in numerical approximations and process simplifications, leading to different numerical codes that ostensibly represent the same underlying dynamics. We consider model-structure inference as a two-step methodology: the first step is to perform system identification on numerical codes for which it is possible to observe the full "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1803.03731","kind":"arxiv","version":2},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"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":"1803.03731","created_at":"2026-05-17T23:55:03.569003+00:00"},{"alias_kind":"arxiv_version","alias_value":"1803.03731v2","created_at":"2026-05-17T23:55:03.569003+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1803.03731","created_at":"2026-05-17T23:55:03.569003+00:00"},{"alias_kind":"pith_short_12","alias_value":"AR6JWG5D7BXH","created_at":"2026-05-18T12:32:13.499390+00:00"},{"alias_kind":"pith_short_16","alias_value":"AR6JWG5D7BXHLTW6","created_at":"2026-05-18T12:32:13.499390+00:00"},{"alias_kind":"pith_short_8","alias_value":"AR6JWG5D","created_at":"2026-05-18T12:32:13.499390+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/AR6JWG5D7BXHLTW62UQVYBITUP","json":"https://pith.science/pith/AR6JWG5D7BXHLTW62UQVYBITUP.json","graph_json":"https://pith.science/api/pith-number/AR6JWG5D7BXHLTW62UQVYBITUP/graph.json","events_json":"https://pith.science/api/pith-number/AR6JWG5D7BXHLTW62UQVYBITUP/events.json","paper":"https://pith.science/paper/AR6JWG5D"},"agent_actions":{"view_html":"https://pith.science/pith/AR6JWG5D7BXHLTW62UQVYBITUP","download_json":"https://pith.science/pith/AR6JWG5D7BXHLTW62UQVYBITUP.json","view_paper":"https://pith.science/paper/AR6JWG5D","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1803.03731&json=true","fetch_graph":"https://pith.science/api/pith-number/AR6JWG5D7BXHLTW62UQVYBITUP/graph.json","fetch_events":"https://pith.science/api/pith-number/AR6JWG5D7BXHLTW62UQVYBITUP/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/AR6JWG5D7BXHLTW62UQVYBITUP/action/timestamp_anchor","attest_storage":"https://pith.science/pith/AR6JWG5D7BXHLTW62UQVYBITUP/action/storage_attestation","attest_author":"https://pith.science/pith/AR6JWG5D7BXHLTW62UQVYBITUP/action/author_attestation","sign_citation":"https://pith.science/pith/AR6JWG5D7BXHLTW62UQVYBITUP/action/citation_signature","submit_replication":"https://pith.science/pith/AR6JWG5D7BXHLTW62UQVYBITUP/action/replication_record"}},"created_at":"2026-05-17T23:55:03.569003+00:00","updated_at":"2026-05-17T23:55:03.569003+00:00"}