{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2019:PMYDPR5UIQM2Q2YHY7BBUBW2QL","short_pith_number":"pith:PMYDPR5U","canonical_record":{"source":{"id":"1902.04727","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.AP","submitted_at":"2019-02-13T03:36:16Z","cross_cats_sorted":["nlin.CD"],"title_canon_sha256":"806961f885c5e9fa963693067839ec1b663c4fad862225dcf1165ea8279a1129","abstract_canon_sha256":"2139a758a443914cd2c8e3a75c9833369155103a82bd95c31324248cdf2d97a7"},"schema_version":"1.0"},"canonical_sha256":"7b3037c7b44419a86b07c7c21a06da82d355f10bffdc55ff848882605248780e","source":{"kind":"arxiv","id":"1902.04727","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1902.04727","created_at":"2026-05-17T23:54:06Z"},{"alias_kind":"arxiv_version","alias_value":"1902.04727v1","created_at":"2026-05-17T23:54:06Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1902.04727","created_at":"2026-05-17T23:54:06Z"},{"alias_kind":"pith_short_12","alias_value":"PMYDPR5UIQM2","created_at":"2026-05-18T12:33:24Z"},{"alias_kind":"pith_short_16","alias_value":"PMYDPR5UIQM2Q2YH","created_at":"2026-05-18T12:33:24Z"},{"alias_kind":"pith_short_8","alias_value":"PMYDPR5U","created_at":"2026-05-18T12:33:24Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2019:PMYDPR5UIQM2Q2YHY7BBUBW2QL","target":"record","payload":{"canonical_record":{"source":{"id":"1902.04727","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.AP","submitted_at":"2019-02-13T03:36:16Z","cross_cats_sorted":["nlin.CD"],"title_canon_sha256":"806961f885c5e9fa963693067839ec1b663c4fad862225dcf1165ea8279a1129","abstract_canon_sha256":"2139a758a443914cd2c8e3a75c9833369155103a82bd95c31324248cdf2d97a7"},"schema_version":"1.0"},"canonical_sha256":"7b3037c7b44419a86b07c7c21a06da82d355f10bffdc55ff848882605248780e","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:54:06.172962Z","signature_b64":"fkNTKGJlWrxNUa/9b4BCzyXPDNTKriTXeotryt31kU5w0NBI9RNOEniXCUIkDP8/sc7huhybGLzgAdGH/dYiCg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"7b3037c7b44419a86b07c7c21a06da82d355f10bffdc55ff848882605248780e","last_reissued_at":"2026-05-17T23:54:06.172533Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:54:06.172533Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1902.04727","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":"2026-05-17T23:54:06Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"FJwIE8AgdyBh0LLFDoom+SB6yK00/8cWzVGkARANioARdh2sd1WKe9/QpkK4yBiWKLlFP/3pl+Ezsc/pWJO0DQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-17T22:22:45.853189Z"},"content_sha256":"1e0d70d67bb836db0c8079accf0b8e155ceed7affdfcb6e80bf268805e8f0db8","schema_version":"1.0","event_id":"sha256:1e0d70d67bb836db0c8079accf0b8e155ceed7affdfcb6e80bf268805e8f0db8"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2019:PMYDPR5UIQM2Q2YHY7BBUBW2QL","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"A simple statistical approach to prediction in open high dimensional chaotic systems","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["nlin.CD"],"primary_cat":"stat.AP","authors_text":"M. LuValle","submitted_at":"2019-02-13T03:36:16Z","abstract_excerpt":"Two recent papers on prediction of chaotic systems, one on multi-view embedding1 , and the second on prediction in projection2 provide empirical evidence to support particular prediction methods for chaotic systems. Multi-view embedding1 is a method of using several multivariate time series to come up with an improved embedding based predictor of a chaotic time series. Prediction in projection2 discusses how much smaller embeddings can provide useful prediction even though they may not be able to resolve the dynamics of the system. Both papers invoke a nearest neighbor3, or Lorenz method of An"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1902.04727","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":"2026-05-17T23:54:06Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"rYPOKl9XqLHEcKV1TKTMQZCAXErUkByjGa8db85E+KzKvnEg6WKqIOxpczSCp7ZF5dJ4Jzr9m3IyWeUY1oCSAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-17T22:22:45.854025Z"},"content_sha256":"c16d3f70991040aab1ae6af67b9047a3265f1349498b974f63019a5cdea4f4b8","schema_version":"1.0","event_id":"sha256:c16d3f70991040aab1ae6af67b9047a3265f1349498b974f63019a5cdea4f4b8"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/PMYDPR5UIQM2Q2YHY7BBUBW2QL/bundle.json","state_url":"https://pith.science/pith/PMYDPR5UIQM2Q2YHY7BBUBW2QL/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/PMYDPR5UIQM2Q2YHY7BBUBW2QL/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":"2026-08-17T22:22:45Z","links":{"resolver":"https://pith.science/pith/PMYDPR5UIQM2Q2YHY7BBUBW2QL","bundle":"https://pith.science/pith/PMYDPR5UIQM2Q2YHY7BBUBW2QL/bundle.json","state":"https://pith.science/pith/PMYDPR5UIQM2Q2YHY7BBUBW2QL/state.json","well_known_bundle":"https://pith.science/.well-known/pith/PMYDPR5UIQM2Q2YHY7BBUBW2QL/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:PMYDPR5UIQM2Q2YHY7BBUBW2QL","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":"2139a758a443914cd2c8e3a75c9833369155103a82bd95c31324248cdf2d97a7","cross_cats_sorted":["nlin.CD"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.AP","submitted_at":"2019-02-13T03:36:16Z","title_canon_sha256":"806961f885c5e9fa963693067839ec1b663c4fad862225dcf1165ea8279a1129"},"schema_version":"1.0","source":{"id":"1902.04727","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1902.04727","created_at":"2026-05-17T23:54:06Z"},{"alias_kind":"arxiv_version","alias_value":"1902.04727v1","created_at":"2026-05-17T23:54:06Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1902.04727","created_at":"2026-05-17T23:54:06Z"},{"alias_kind":"pith_short_12","alias_value":"PMYDPR5UIQM2","created_at":"2026-05-18T12:33:24Z"},{"alias_kind":"pith_short_16","alias_value":"PMYDPR5UIQM2Q2YH","created_at":"2026-05-18T12:33:24Z"},{"alias_kind":"pith_short_8","alias_value":"PMYDPR5U","created_at":"2026-05-18T12:33:24Z"}],"graph_snapshots":[{"event_id":"sha256:c16d3f70991040aab1ae6af67b9047a3265f1349498b974f63019a5cdea4f4b8","target":"graph","created_at":"2026-05-17T23:54:06Z","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":"Two recent papers on prediction of chaotic systems, one on multi-view embedding1 , and the second on prediction in projection2 provide empirical evidence to support particular prediction methods for chaotic systems. Multi-view embedding1 is a method of using several multivariate time series to come up with an improved embedding based predictor of a chaotic time series. Prediction in projection2 discusses how much smaller embeddings can provide useful prediction even though they may not be able to resolve the dynamics of the system. Both papers invoke a nearest neighbor3, or Lorenz method of An","authors_text":"M. LuValle","cross_cats":["nlin.CD"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.AP","submitted_at":"2019-02-13T03:36:16Z","title":"A simple statistical approach to prediction in open high dimensional chaotic systems"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1902.04727","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":"sha256:1e0d70d67bb836db0c8079accf0b8e155ceed7affdfcb6e80bf268805e8f0db8","target":"record","created_at":"2026-05-17T23:54:06Z","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":"2139a758a443914cd2c8e3a75c9833369155103a82bd95c31324248cdf2d97a7","cross_cats_sorted":["nlin.CD"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.AP","submitted_at":"2019-02-13T03:36:16Z","title_canon_sha256":"806961f885c5e9fa963693067839ec1b663c4fad862225dcf1165ea8279a1129"},"schema_version":"1.0","source":{"id":"1902.04727","kind":"arxiv","version":1}},"canonical_sha256":"7b3037c7b44419a86b07c7c21a06da82d355f10bffdc55ff848882605248780e","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"7b3037c7b44419a86b07c7c21a06da82d355f10bffdc55ff848882605248780e","first_computed_at":"2026-05-17T23:54:06.172533Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:54:06.172533Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"fkNTKGJlWrxNUa/9b4BCzyXPDNTKriTXeotryt31kU5w0NBI9RNOEniXCUIkDP8/sc7huhybGLzgAdGH/dYiCg==","signature_status":"signed_v1","signed_at":"2026-05-17T23:54:06.172962Z","signed_message":"canonical_sha256_bytes"},"source_id":"1902.04727","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:1e0d70d67bb836db0c8079accf0b8e155ceed7affdfcb6e80bf268805e8f0db8","sha256:c16d3f70991040aab1ae6af67b9047a3265f1349498b974f63019a5cdea4f4b8"],"state_sha256":"d8d1eae50724a13c940d28ceb1bd1903dc8ee155f659fe12df33dbd72ac325d6"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"7/rVkAQr+GXVHi99N+OmPMBXd56Phw37JKg2b555gc+rsOjYFus5OEzgKOypWZx23NxdoNGtN1SSGnlnqI9mAw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-17T22:22:45.866980Z","bundle_sha256":"3582e32ccc01174ef36277d0c21957853b1a5d7aa492b2664120d1e6ccef935f"}}