{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2014:SFDTKTOOSMCY5KUIO7DNKRL3RM","short_pith_number":"pith:SFDTKTOO","canonical_record":{"source":{"id":"1411.0793","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.ST","submitted_at":"2014-11-04T05:55:27Z","cross_cats_sorted":["stat.TH"],"title_canon_sha256":"deefcec01ed52373802d1a33e75879e3bb8914d34bb307dbe601e0d272ee3db5","abstract_canon_sha256":"acb7827bcc19810ce5916b23b0bde51ad308a1a947b584f4561254191fb96d63"},"schema_version":"1.0"},"canonical_sha256":"9147354dce93058eaa8877c6d5457b8b04bc6b186ead16086f8fed75a16733f2","source":{"kind":"arxiv","id":"1411.0793","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1411.0793","created_at":"2026-05-18T02:38:38Z"},{"alias_kind":"arxiv_version","alias_value":"1411.0793v1","created_at":"2026-05-18T02:38:38Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1411.0793","created_at":"2026-05-18T02:38:38Z"},{"alias_kind":"pith_short_12","alias_value":"SFDTKTOOSMCY","created_at":"2026-05-18T12:28:49Z"},{"alias_kind":"pith_short_16","alias_value":"SFDTKTOOSMCY5KUI","created_at":"2026-05-18T12:28:49Z"},{"alias_kind":"pith_short_8","alias_value":"SFDTKTOO","created_at":"2026-05-18T12:28:49Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2014:SFDTKTOOSMCY5KUIO7DNKRL3RM","target":"record","payload":{"canonical_record":{"source":{"id":"1411.0793","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.ST","submitted_at":"2014-11-04T05:55:27Z","cross_cats_sorted":["stat.TH"],"title_canon_sha256":"deefcec01ed52373802d1a33e75879e3bb8914d34bb307dbe601e0d272ee3db5","abstract_canon_sha256":"acb7827bcc19810ce5916b23b0bde51ad308a1a947b584f4561254191fb96d63"},"schema_version":"1.0"},"canonical_sha256":"9147354dce93058eaa8877c6d5457b8b04bc6b186ead16086f8fed75a16733f2","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T02:38:38.249589Z","signature_b64":"YoedeeE5iVwSLMuBqUnk1MpKpyO+BYwNzazlRN18v74SyHLBPwORpXrS9Q0IPThJDV9KxiAeszgB/kGvPDvSBg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"9147354dce93058eaa8877c6d5457b8b04bc6b186ead16086f8fed75a16733f2","last_reissued_at":"2026-05-18T02:38:38.249072Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T02:38:38.249072Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1411.0793","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":"2026-05-18T02:38:38Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"L76fI0/D2xgGQXsLq9Y+AU06OfV27Er4n+Is7vgesvICLU3amq759AqBSunHG/Ne6Wot37nXeJhDvoMFprAGDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-10T11:58:12.318719Z"},"content_sha256":"fa54338c13250d970ee6ab89f338fbdc6f4dbb34e36d1c5f5dfb61b852b2eca6","schema_version":"1.0","event_id":"sha256:fa54338c13250d970ee6ab89f338fbdc6f4dbb34e36d1c5f5dfb61b852b2eca6"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2014:SFDTKTOOSMCY5KUIO7DNKRL3RM","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Bayesian two-step estimation in differential equation models","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.TH"],"primary_cat":"math.ST","authors_text":"Prithwish Bhaumik, Subhashis Ghosal","submitted_at":"2014-11-04T05:55:27Z","abstract_excerpt":"Ordinary differential equations (ODEs) are used to model dynamic systems appearing in engineering, physics, biomedical sciences and many other fields. These equations contain unknown parameters, say $\\bm\\theta$ of physical significance which have to be estimated from the noisy data. Often there is no closed form analytic solution of the equations and hence we cannot use the usual non-linear least squares technique to estimate the unknown parameters. There is a two-step approach to solve this problem, where the first step involves fitting the data nonparametrically. In the second step the param"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1411.0793","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":""},"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":"2026-05-18T02:38:38Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"nQuoCW42NdFoFQ/yWnSYFzHkCkuMPjoH08AnpKTloocG//b7Td7SPoYSL4kJx6hICObXV5Yf0Q1o2jF8aa0xCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-10T11:58:12.319486Z"},"content_sha256":"67842bbeff252420ef124d41b59627c57aa7a8ab01d1afa6798dcae50782b6a2","schema_version":"1.0","event_id":"sha256:67842bbeff252420ef124d41b59627c57aa7a8ab01d1afa6798dcae50782b6a2"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/SFDTKTOOSMCY5KUIO7DNKRL3RM/bundle.json","state_url":"https://pith.science/pith/SFDTKTOOSMCY5KUIO7DNKRL3RM/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/SFDTKTOOSMCY5KUIO7DNKRL3RM/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":"2026-06-10T11:58:12Z","links":{"resolver":"https://pith.science/pith/SFDTKTOOSMCY5KUIO7DNKRL3RM","bundle":"https://pith.science/pith/SFDTKTOOSMCY5KUIO7DNKRL3RM/bundle.json","state":"https://pith.science/pith/SFDTKTOOSMCY5KUIO7DNKRL3RM/state.json","well_known_bundle":"https://pith.science/.well-known/pith/SFDTKTOOSMCY5KUIO7DNKRL3RM/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2014:SFDTKTOOSMCY5KUIO7DNKRL3RM","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":"acb7827bcc19810ce5916b23b0bde51ad308a1a947b584f4561254191fb96d63","cross_cats_sorted":["stat.TH"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.ST","submitted_at":"2014-11-04T05:55:27Z","title_canon_sha256":"deefcec01ed52373802d1a33e75879e3bb8914d34bb307dbe601e0d272ee3db5"},"schema_version":"1.0","source":{"id":"1411.0793","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1411.0793","created_at":"2026-05-18T02:38:38Z"},{"alias_kind":"arxiv_version","alias_value":"1411.0793v1","created_at":"2026-05-18T02:38:38Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1411.0793","created_at":"2026-05-18T02:38:38Z"},{"alias_kind":"pith_short_12","alias_value":"SFDTKTOOSMCY","created_at":"2026-05-18T12:28:49Z"},{"alias_kind":"pith_short_16","alias_value":"SFDTKTOOSMCY5KUI","created_at":"2026-05-18T12:28:49Z"},{"alias_kind":"pith_short_8","alias_value":"SFDTKTOO","created_at":"2026-05-18T12:28:49Z"}],"graph_snapshots":[{"event_id":"sha256:67842bbeff252420ef124d41b59627c57aa7a8ab01d1afa6798dcae50782b6a2","target":"graph","created_at":"2026-05-18T02:38:38Z","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"},"paper":{"abstract_excerpt":"Ordinary differential equations (ODEs) are used to model dynamic systems appearing in engineering, physics, biomedical sciences and many other fields. These equations contain unknown parameters, say $\\bm\\theta$ of physical significance which have to be estimated from the noisy data. Often there is no closed form analytic solution of the equations and hence we cannot use the usual non-linear least squares technique to estimate the unknown parameters. There is a two-step approach to solve this problem, where the first step involves fitting the data nonparametrically. In the second step the param","authors_text":"Prithwish Bhaumik, Subhashis Ghosal","cross_cats":["stat.TH"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.ST","submitted_at":"2014-11-04T05:55:27Z","title":"Bayesian two-step estimation in differential equation models"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1411.0793","kind":"arxiv","version":1},"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:fa54338c13250d970ee6ab89f338fbdc6f4dbb34e36d1c5f5dfb61b852b2eca6","target":"record","created_at":"2026-05-18T02:38:38Z","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":"acb7827bcc19810ce5916b23b0bde51ad308a1a947b584f4561254191fb96d63","cross_cats_sorted":["stat.TH"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.ST","submitted_at":"2014-11-04T05:55:27Z","title_canon_sha256":"deefcec01ed52373802d1a33e75879e3bb8914d34bb307dbe601e0d272ee3db5"},"schema_version":"1.0","source":{"id":"1411.0793","kind":"arxiv","version":1}},"canonical_sha256":"9147354dce93058eaa8877c6d5457b8b04bc6b186ead16086f8fed75a16733f2","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"9147354dce93058eaa8877c6d5457b8b04bc6b186ead16086f8fed75a16733f2","first_computed_at":"2026-05-18T02:38:38.249072Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T02:38:38.249072Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"YoedeeE5iVwSLMuBqUnk1MpKpyO+BYwNzazlRN18v74SyHLBPwORpXrS9Q0IPThJDV9KxiAeszgB/kGvPDvSBg==","signature_status":"signed_v1","signed_at":"2026-05-18T02:38:38.249589Z","signed_message":"canonical_sha256_bytes"},"source_id":"1411.0793","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:fa54338c13250d970ee6ab89f338fbdc6f4dbb34e36d1c5f5dfb61b852b2eca6","sha256:67842bbeff252420ef124d41b59627c57aa7a8ab01d1afa6798dcae50782b6a2"],"state_sha256":"9c1de9f988a2ca315c035a2b3cb778e206d73682d5edc7f977b25afdf87c5325"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"1ZSozjgoBuxDkRLCC2Tk820OUnGT+uPoNfnj2lZAZEgwcp6m+DAJBYbEB7PGcqJ1obGjTYMkogjQXISBLDodBw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-10T11:58:12.324156Z","bundle_sha256":"b3cc52df308c52c4b1d62de3d475210050ee86b697afec42587983278e98efa6"}}