{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:5IXS25ACDNMW5LYAJJ7SSFLPTD","short_pith_number":"pith:5IXS25AC","canonical_record":{"source":{"id":"2510.24539","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"stat.ME","submitted_at":"2025-10-28T15:42:29Z","cross_cats_sorted":[],"title_canon_sha256":"f6f83a03f66a7778cc894f3f858dc785a8898936307681cb0518dc295f835c17","abstract_canon_sha256":"0b909816d2fc5696aab15da9e3e1f640f62b70b5c506cb451a71819b47972dbb"},"schema_version":"1.0"},"canonical_sha256":"ea2f2d74021b596eaf004a7f29156f98d2806c9ebef21247b802b50baf7d0a8d","source":{"kind":"arxiv","id":"2510.24539","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2510.24539","created_at":"2026-05-20T00:00:26Z"},{"alias_kind":"arxiv_version","alias_value":"2510.24539v2","created_at":"2026-05-20T00:00:26Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2510.24539","created_at":"2026-05-20T00:00:26Z"},{"alias_kind":"pith_short_12","alias_value":"5IXS25ACDNMW","created_at":"2026-05-20T00:00:26Z"},{"alias_kind":"pith_short_16","alias_value":"5IXS25ACDNMW5LYA","created_at":"2026-05-20T00:00:26Z"},{"alias_kind":"pith_short_8","alias_value":"5IXS25AC","created_at":"2026-05-20T00:00:26Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:5IXS25ACDNMW5LYAJJ7SSFLPTD","target":"record","payload":{"canonical_record":{"source":{"id":"2510.24539","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"stat.ME","submitted_at":"2025-10-28T15:42:29Z","cross_cats_sorted":[],"title_canon_sha256":"f6f83a03f66a7778cc894f3f858dc785a8898936307681cb0518dc295f835c17","abstract_canon_sha256":"0b909816d2fc5696aab15da9e3e1f640f62b70b5c506cb451a71819b47972dbb"},"schema_version":"1.0"},"canonical_sha256":"ea2f2d74021b596eaf004a7f29156f98d2806c9ebef21247b802b50baf7d0a8d","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-20T00:00:26.752541Z","signature_b64":"WkEwG4Oqy7+kEvKKF4ggLOh8x7DAlJCEgXD/N3NCpg1CaEnplBDI+StLQARB/5qyh0KK21/35+FXyr6tSXONDw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"ea2f2d74021b596eaf004a7f29156f98d2806c9ebef21247b802b50baf7d0a8d","last_reissued_at":"2026-05-20T00:00:26.751725Z","signature_status":"signed_v1","first_computed_at":"2026-05-20T00:00:26.751725Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2510.24539","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-20T00:00:26Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"a5ClH6CvbADJ9qw+SiOkI40IvvcNMUZ8CUcpeNt3RfFlkp+KRLz7ZyXrr5No3wP5jrhX9YBX3Yc1pXxkbGt1DQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-27T23:24:29.692146Z"},"content_sha256":"dbed0713183ee7ba9d1ad66362f1c6d2357de47e92ca6da2a95fbddee25ee7f4","schema_version":"1.0","event_id":"sha256:dbed0713183ee7ba9d1ad66362f1c6d2357de47e92ca6da2a95fbddee25ee7f4"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:5IXS25ACDNMW5LYAJJ7SSFLPTD","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Unbiased likelihood estimation of the Langevin diffusion for animal movement modelling","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":[],"primary_cat":"stat.ME","authors_text":"Martin E. Pettersen, Robert B. O'Hara, Ron R. Togunov, S. Knutsen Furset","submitted_at":"2025-10-28T15:42:29Z","abstract_excerpt":"An ongoing challenge in animal ecology is developing movement models that account for the autocorrelation, and often temporal irregularity, in telemetry data. Continuous-time Langevin diffusion models have been proposed to model temporally autocorrelated and irregularly sampled data. However, current estimation techniques obtain increasingly biased parameter estimates as the time between observations increases. In this paper, we propose using Brownian bridges in an importance sampling scheme to improve the likelihood approximation of the Langevin diffusion model. In a series of simulation stud"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2510.24539","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":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2510.24539/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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-20T00:00:26Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"QtlJGp5RkdLxBedG9Uzt2jk/9AGz9MTNqEZ21q1nhRMcWl9bDFdpHO4VHxYlgVNbmjKHfq6ARyBiZqiOHTFVDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-27T23:24:29.692679Z"},"content_sha256":"bdd3f0151a2f72ecf1a153c3eed27ef2fecaa8421a0470fb6a9c23e3d9ec680d","schema_version":"1.0","event_id":"sha256:bdd3f0151a2f72ecf1a153c3eed27ef2fecaa8421a0470fb6a9c23e3d9ec680d"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/5IXS25ACDNMW5LYAJJ7SSFLPTD/bundle.json","state_url":"https://pith.science/pith/5IXS25ACDNMW5LYAJJ7SSFLPTD/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/5IXS25ACDNMW5LYAJJ7SSFLPTD/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":"2026-05-27T23:24:29Z","links":{"resolver":"https://pith.science/pith/5IXS25ACDNMW5LYAJJ7SSFLPTD","bundle":"https://pith.science/pith/5IXS25ACDNMW5LYAJJ7SSFLPTD/bundle.json","state":"https://pith.science/pith/5IXS25ACDNMW5LYAJJ7SSFLPTD/state.json","well_known_bundle":"https://pith.science/.well-known/pith/5IXS25ACDNMW5LYAJJ7SSFLPTD/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:5IXS25ACDNMW5LYAJJ7SSFLPTD","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":"0b909816d2fc5696aab15da9e3e1f640f62b70b5c506cb451a71819b47972dbb","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"stat.ME","submitted_at":"2025-10-28T15:42:29Z","title_canon_sha256":"f6f83a03f66a7778cc894f3f858dc785a8898936307681cb0518dc295f835c17"},"schema_version":"1.0","source":{"id":"2510.24539","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2510.24539","created_at":"2026-05-20T00:00:26Z"},{"alias_kind":"arxiv_version","alias_value":"2510.24539v2","created_at":"2026-05-20T00:00:26Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2510.24539","created_at":"2026-05-20T00:00:26Z"},{"alias_kind":"pith_short_12","alias_value":"5IXS25ACDNMW","created_at":"2026-05-20T00:00:26Z"},{"alias_kind":"pith_short_16","alias_value":"5IXS25ACDNMW5LYA","created_at":"2026-05-20T00:00:26Z"},{"alias_kind":"pith_short_8","alias_value":"5IXS25AC","created_at":"2026-05-20T00:00:26Z"}],"graph_snapshots":[{"event_id":"sha256:bdd3f0151a2f72ecf1a153c3eed27ef2fecaa8421a0470fb6a9c23e3d9ec680d","target":"graph","created_at":"2026-05-20T00:00:26Z","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"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2510.24539/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"An ongoing challenge in animal ecology is developing movement models that account for the autocorrelation, and often temporal irregularity, in telemetry data. Continuous-time Langevin diffusion models have been proposed to model temporally autocorrelated and irregularly sampled data. However, current estimation techniques obtain increasingly biased parameter estimates as the time between observations increases. In this paper, we propose using Brownian bridges in an importance sampling scheme to improve the likelihood approximation of the Langevin diffusion model. In a series of simulation stud","authors_text":"Martin E. Pettersen, Robert B. O'Hara, Ron R. Togunov, S. Knutsen Furset","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"stat.ME","submitted_at":"2025-10-28T15:42:29Z","title":"Unbiased likelihood estimation of the Langevin diffusion for animal movement modelling"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2510.24539","kind":"arxiv","version":2},"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:dbed0713183ee7ba9d1ad66362f1c6d2357de47e92ca6da2a95fbddee25ee7f4","target":"record","created_at":"2026-05-20T00:00:26Z","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":"0b909816d2fc5696aab15da9e3e1f640f62b70b5c506cb451a71819b47972dbb","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"stat.ME","submitted_at":"2025-10-28T15:42:29Z","title_canon_sha256":"f6f83a03f66a7778cc894f3f858dc785a8898936307681cb0518dc295f835c17"},"schema_version":"1.0","source":{"id":"2510.24539","kind":"arxiv","version":2}},"canonical_sha256":"ea2f2d74021b596eaf004a7f29156f98d2806c9ebef21247b802b50baf7d0a8d","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"ea2f2d74021b596eaf004a7f29156f98d2806c9ebef21247b802b50baf7d0a8d","first_computed_at":"2026-05-20T00:00:26.751725Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-20T00:00:26.751725Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"WkEwG4Oqy7+kEvKKF4ggLOh8x7DAlJCEgXD/N3NCpg1CaEnplBDI+StLQARB/5qyh0KK21/35+FXyr6tSXONDw==","signature_status":"signed_v1","signed_at":"2026-05-20T00:00:26.752541Z","signed_message":"canonical_sha256_bytes"},"source_id":"2510.24539","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:dbed0713183ee7ba9d1ad66362f1c6d2357de47e92ca6da2a95fbddee25ee7f4","sha256:bdd3f0151a2f72ecf1a153c3eed27ef2fecaa8421a0470fb6a9c23e3d9ec680d"],"state_sha256":"d4dd0bbc50a2b78f5cdb554d5c05ca68b1fc1a64180298d1a17d8752794d3eef"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Ypmc7f9B7pX3AJVrZB12A1hf23/w1zk47dP56zwEWVw3H6u7Ma1Nxx2RxRaWTCRARMNkcoO/hraHADdokW99Ag==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-27T23:24:29.695494Z","bundle_sha256":"482051276ffd7b23f19e146627feddbdf275be1f28e5ebae5d2ed42f63c8fd3b"}}