{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2017:D3WZ3SWYISABUOVGR55QS7QQVE","short_pith_number":"pith:D3WZ3SWY","canonical_record":{"source":{"id":"1709.02404","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.AP","submitted_at":"2017-09-07T18:42:12Z","cross_cats_sorted":[],"title_canon_sha256":"d4b81f9b4e0dc73ec0924da780f762d988519a52912627cc924871e4a87d6349","abstract_canon_sha256":"2f3ff0d2abdb67af51503129b5e3af40e8858bb839236590319b0c2f0377295b"},"schema_version":"1.0"},"canonical_sha256":"1eed9dcad844801a3aa68f7b097e10a91510f139f31d2ae3c2a45f9ac14ba65d","source":{"kind":"arxiv","id":"1709.02404","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1709.02404","created_at":"2026-05-18T00:35:45Z"},{"alias_kind":"arxiv_version","alias_value":"1709.02404v1","created_at":"2026-05-18T00:35:45Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1709.02404","created_at":"2026-05-18T00:35:45Z"},{"alias_kind":"pith_short_12","alias_value":"D3WZ3SWYISAB","created_at":"2026-05-18T12:31:10Z"},{"alias_kind":"pith_short_16","alias_value":"D3WZ3SWYISABUOVG","created_at":"2026-05-18T12:31:10Z"},{"alias_kind":"pith_short_8","alias_value":"D3WZ3SWY","created_at":"2026-05-18T12:31:10Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2017:D3WZ3SWYISABUOVGR55QS7QQVE","target":"record","payload":{"canonical_record":{"source":{"id":"1709.02404","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.AP","submitted_at":"2017-09-07T18:42:12Z","cross_cats_sorted":[],"title_canon_sha256":"d4b81f9b4e0dc73ec0924da780f762d988519a52912627cc924871e4a87d6349","abstract_canon_sha256":"2f3ff0d2abdb67af51503129b5e3af40e8858bb839236590319b0c2f0377295b"},"schema_version":"1.0"},"canonical_sha256":"1eed9dcad844801a3aa68f7b097e10a91510f139f31d2ae3c2a45f9ac14ba65d","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:35:45.960172Z","signature_b64":"lISV/ThfXZELMdr8MFk8Nr9hyCb6E8iv5k/MtRXVpni8Czl3HALssPnVcCvULd++xz8SxTHciRBZiouvj+mdCw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"1eed9dcad844801a3aa68f7b097e10a91510f139f31d2ae3c2a45f9ac14ba65d","last_reissued_at":"2026-05-18T00:35:45.959676Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:35:45.959676Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1709.02404","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":"2026-05-18T00:35:45Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Wzc3eo9AjZ+a6RojugAkBOhHoHCK0NhUSJCZCB6KwRXnPVYXgpelL6j7Kbw+aw2yT7C7p506nQxxM6iOISeTCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-11T11:57:14.100609Z"},"content_sha256":"e61b1ee87009f573716723d8d213fe9a8aefad4a8a12169e2f276cb3e3444237","schema_version":"1.0","event_id":"sha256:e61b1ee87009f573716723d8d213fe9a8aefad4a8a12169e2f276cb3e3444237"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2017:D3WZ3SWYISABUOVGR55QS7QQVE","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"EMD-regression for modelling multi-scale relationships, and application to weather-related cardiovascular mortality","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"stat.AP","authors_text":"Andr\\'e St-Hilaire, Belkacem Abdous, Diane B\\'elanger, Fateh Chebana, Pierre Gosselin, Pierre Masselot, Taha B.M.J. Ouarda","submitted_at":"2017-09-07T18:42:12Z","abstract_excerpt":"In a number of environmental studies, relationships between natural processes are often assessed through regression analyses, using time series data. Such data are often multi-scale and non-stationary, leading to a poor accuracy of the resulting regression models and therefore to results with moderate reliability. To deal with this issue, the present paper introduces the EMD-regression methodology consisting in applying the empirical mode decomposition (EMD) algorithm on data series and then using the resulting components in regression models. The proposed methodology presents a number of adva"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1709.02404","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":"2026-05-18T00:35:45Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"64hJQfHp08G7yq+X0qi/kw5/wc2sGTqFE3bWQUZd6+73dILGWGWuaK2qp0A0vpmWwae749c5xTaEn78r2xU6DQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-11T11:57:14.100959Z"},"content_sha256":"cac372f84853b999582bdca2c66b873d6ab190052dfb82a3afd1b90ea18eccd6","schema_version":"1.0","event_id":"sha256:cac372f84853b999582bdca2c66b873d6ab190052dfb82a3afd1b90ea18eccd6"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/D3WZ3SWYISABUOVGR55QS7QQVE/bundle.json","state_url":"https://pith.science/pith/D3WZ3SWYISABUOVGR55QS7QQVE/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/D3WZ3SWYISABUOVGR55QS7QQVE/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":"2026-06-11T11:57:14Z","links":{"resolver":"https://pith.science/pith/D3WZ3SWYISABUOVGR55QS7QQVE","bundle":"https://pith.science/pith/D3WZ3SWYISABUOVGR55QS7QQVE/bundle.json","state":"https://pith.science/pith/D3WZ3SWYISABUOVGR55QS7QQVE/state.json","well_known_bundle":"https://pith.science/.well-known/pith/D3WZ3SWYISABUOVGR55QS7QQVE/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2017:D3WZ3SWYISABUOVGR55QS7QQVE","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":"2f3ff0d2abdb67af51503129b5e3af40e8858bb839236590319b0c2f0377295b","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.AP","submitted_at":"2017-09-07T18:42:12Z","title_canon_sha256":"d4b81f9b4e0dc73ec0924da780f762d988519a52912627cc924871e4a87d6349"},"schema_version":"1.0","source":{"id":"1709.02404","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1709.02404","created_at":"2026-05-18T00:35:45Z"},{"alias_kind":"arxiv_version","alias_value":"1709.02404v1","created_at":"2026-05-18T00:35:45Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1709.02404","created_at":"2026-05-18T00:35:45Z"},{"alias_kind":"pith_short_12","alias_value":"D3WZ3SWYISAB","created_at":"2026-05-18T12:31:10Z"},{"alias_kind":"pith_short_16","alias_value":"D3WZ3SWYISABUOVG","created_at":"2026-05-18T12:31:10Z"},{"alias_kind":"pith_short_8","alias_value":"D3WZ3SWY","created_at":"2026-05-18T12:31:10Z"}],"graph_snapshots":[{"event_id":"sha256:cac372f84853b999582bdca2c66b873d6ab190052dfb82a3afd1b90ea18eccd6","target":"graph","created_at":"2026-05-18T00:35:45Z","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":"In a number of environmental studies, relationships between natural processes are often assessed through regression analyses, using time series data. Such data are often multi-scale and non-stationary, leading to a poor accuracy of the resulting regression models and therefore to results with moderate reliability. To deal with this issue, the present paper introduces the EMD-regression methodology consisting in applying the empirical mode decomposition (EMD) algorithm on data series and then using the resulting components in regression models. The proposed methodology presents a number of adva","authors_text":"Andr\\'e St-Hilaire, Belkacem Abdous, Diane B\\'elanger, Fateh Chebana, Pierre Gosselin, Pierre Masselot, Taha B.M.J. Ouarda","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.AP","submitted_at":"2017-09-07T18:42:12Z","title":"EMD-regression for modelling multi-scale relationships, and application to weather-related cardiovascular mortality"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1709.02404","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:e61b1ee87009f573716723d8d213fe9a8aefad4a8a12169e2f276cb3e3444237","target":"record","created_at":"2026-05-18T00:35:45Z","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":"2f3ff0d2abdb67af51503129b5e3af40e8858bb839236590319b0c2f0377295b","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.AP","submitted_at":"2017-09-07T18:42:12Z","title_canon_sha256":"d4b81f9b4e0dc73ec0924da780f762d988519a52912627cc924871e4a87d6349"},"schema_version":"1.0","source":{"id":"1709.02404","kind":"arxiv","version":1}},"canonical_sha256":"1eed9dcad844801a3aa68f7b097e10a91510f139f31d2ae3c2a45f9ac14ba65d","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"1eed9dcad844801a3aa68f7b097e10a91510f139f31d2ae3c2a45f9ac14ba65d","first_computed_at":"2026-05-18T00:35:45.959676Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:35:45.959676Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"lISV/ThfXZELMdr8MFk8Nr9hyCb6E8iv5k/MtRXVpni8Czl3HALssPnVcCvULd++xz8SxTHciRBZiouvj+mdCw==","signature_status":"signed_v1","signed_at":"2026-05-18T00:35:45.960172Z","signed_message":"canonical_sha256_bytes"},"source_id":"1709.02404","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:e61b1ee87009f573716723d8d213fe9a8aefad4a8a12169e2f276cb3e3444237","sha256:cac372f84853b999582bdca2c66b873d6ab190052dfb82a3afd1b90ea18eccd6"],"state_sha256":"80d0c32cf0471b6d32419e03e9e38cceacf3de6a66320b3f150b62ad86017cba"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"r2pPo9HHWvPICQYnHaKmgg3BKzoq1JK5PaSoVqPAYmzL4OkHnFpaKE5OooGLQIpXQVuNH52AWF2kiQwqrYURDw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-11T11:57:14.102866Z","bundle_sha256":"a07780ffee62b0760d9c94e480f03900634198bdd3306a1fa68c05d0468ed448"}}