{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2015:LQYQ5B2FCXALXO7I6LFVJZCOFY","short_pith_number":"pith:LQYQ5B2F","canonical_record":{"source":{"id":"1509.01171","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ME","submitted_at":"2015-09-03T17:28:45Z","cross_cats_sorted":[],"title_canon_sha256":"d6f5aee02f6ad5a2925fb150fb97ee3299597bb288252a478d884364b06afeed","abstract_canon_sha256":"c6ac3bcf87d2180e6b50d406a1a4ff5c137b1b6e17819d07e71454412c55012a"},"schema_version":"1.0"},"canonical_sha256":"5c310e874515c0bbbbe8f2cb54e44e2e27204221c182e3b6c52004dbcc93f03e","source":{"kind":"arxiv","id":"1509.01171","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1509.01171","created_at":"2026-05-18T01:34:04Z"},{"alias_kind":"arxiv_version","alias_value":"1509.01171v1","created_at":"2026-05-18T01:34:04Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1509.01171","created_at":"2026-05-18T01:34:04Z"},{"alias_kind":"pith_short_12","alias_value":"LQYQ5B2FCXAL","created_at":"2026-05-18T12:29:29Z"},{"alias_kind":"pith_short_16","alias_value":"LQYQ5B2FCXALXO7I","created_at":"2026-05-18T12:29:29Z"},{"alias_kind":"pith_short_8","alias_value":"LQYQ5B2F","created_at":"2026-05-18T12:29:29Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2015:LQYQ5B2FCXALXO7I6LFVJZCOFY","target":"record","payload":{"canonical_record":{"source":{"id":"1509.01171","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ME","submitted_at":"2015-09-03T17:28:45Z","cross_cats_sorted":[],"title_canon_sha256":"d6f5aee02f6ad5a2925fb150fb97ee3299597bb288252a478d884364b06afeed","abstract_canon_sha256":"c6ac3bcf87d2180e6b50d406a1a4ff5c137b1b6e17819d07e71454412c55012a"},"schema_version":"1.0"},"canonical_sha256":"5c310e874515c0bbbbe8f2cb54e44e2e27204221c182e3b6c52004dbcc93f03e","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T01:34:04.171913Z","signature_b64":"bdirrBh22wIt76QJJaHK2pL8m0TUovOLhU8D1fQJEsDx8QEg0wft9bIO32upwPiSUCQzFeBxuhJEy6jHTQTLDQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"5c310e874515c0bbbbe8f2cb54e44e2e27204221c182e3b6c52004dbcc93f03e","last_reissued_at":"2026-05-18T01:34:04.171304Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T01:34:04.171304Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1509.01171","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":"2026-05-18T01:34:04Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"qgHxM/W9HTPg/gZfztnobToLDu+CiHcFnfor4sHQPNaSiAzRo2AVmV75wHTf18vispGIa80nOIPNPVIQbyr3Ag==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-07T23:25:12.024809Z"},"content_sha256":"a84795a4a0fb30689254aff5bf18f528cbd3b6c53be190457fb01e516f04dd89","schema_version":"1.0","event_id":"sha256:a84795a4a0fb30689254aff5bf18f528cbd3b6c53be190457fb01e516f04dd89"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2015:LQYQ5B2FCXALXO7I6LFVJZCOFY","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"A novel principal component analysis for spatially-misaligned multivariate air pollution data","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"stat.ME","authors_text":"Adam A. Szpiro, Lianne A. Sheppard, Paul D. Sampson, Roman A. Jandarov","submitted_at":"2015-09-03T17:28:45Z","abstract_excerpt":"We propose novel methods for predictive (sparse) PCA with spatially misaligned data. These methods identify principal component loading vectors that explain as much variability in the observed data as possible, while also ensuring the corresponding principal component scores can be predicted accurately by means of spatial statistics at locations where air pollution measurements are not available. This will make it possible to identify important mixtures of air pollutants and to quantify their health effects in cohort studies, where currently available methods cannot be used. We demonstrate the"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1509.01171","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":"2026-05-18T01:34:04Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"935CtmPcF0bN6rraz1aAHdZKkGzoVE3g4tXzNjGuhj3j21QoeQUvEokpmKvO1K0Rdl4BpHEbFnbiPgYcQvbjBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-07T23:25:12.025548Z"},"content_sha256":"1c5627e1c084023d97e276fd3efac45a5b01ff245b4d731208f54fd1b64be98b","schema_version":"1.0","event_id":"sha256:1c5627e1c084023d97e276fd3efac45a5b01ff245b4d731208f54fd1b64be98b"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/LQYQ5B2FCXALXO7I6LFVJZCOFY/bundle.json","state_url":"https://pith.science/pith/LQYQ5B2FCXALXO7I6LFVJZCOFY/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/LQYQ5B2FCXALXO7I6LFVJZCOFY/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":"2026-06-07T23:25:12Z","links":{"resolver":"https://pith.science/pith/LQYQ5B2FCXALXO7I6LFVJZCOFY","bundle":"https://pith.science/pith/LQYQ5B2FCXALXO7I6LFVJZCOFY/bundle.json","state":"https://pith.science/pith/LQYQ5B2FCXALXO7I6LFVJZCOFY/state.json","well_known_bundle":"https://pith.science/.well-known/pith/LQYQ5B2FCXALXO7I6LFVJZCOFY/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2015:LQYQ5B2FCXALXO7I6LFVJZCOFY","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":"c6ac3bcf87d2180e6b50d406a1a4ff5c137b1b6e17819d07e71454412c55012a","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ME","submitted_at":"2015-09-03T17:28:45Z","title_canon_sha256":"d6f5aee02f6ad5a2925fb150fb97ee3299597bb288252a478d884364b06afeed"},"schema_version":"1.0","source":{"id":"1509.01171","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1509.01171","created_at":"2026-05-18T01:34:04Z"},{"alias_kind":"arxiv_version","alias_value":"1509.01171v1","created_at":"2026-05-18T01:34:04Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1509.01171","created_at":"2026-05-18T01:34:04Z"},{"alias_kind":"pith_short_12","alias_value":"LQYQ5B2FCXAL","created_at":"2026-05-18T12:29:29Z"},{"alias_kind":"pith_short_16","alias_value":"LQYQ5B2FCXALXO7I","created_at":"2026-05-18T12:29:29Z"},{"alias_kind":"pith_short_8","alias_value":"LQYQ5B2F","created_at":"2026-05-18T12:29:29Z"}],"graph_snapshots":[{"event_id":"sha256:1c5627e1c084023d97e276fd3efac45a5b01ff245b4d731208f54fd1b64be98b","target":"graph","created_at":"2026-05-18T01:34:04Z","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":"We propose novel methods for predictive (sparse) PCA with spatially misaligned data. These methods identify principal component loading vectors that explain as much variability in the observed data as possible, while also ensuring the corresponding principal component scores can be predicted accurately by means of spatial statistics at locations where air pollution measurements are not available. This will make it possible to identify important mixtures of air pollutants and to quantify their health effects in cohort studies, where currently available methods cannot be used. We demonstrate the","authors_text":"Adam A. Szpiro, Lianne A. Sheppard, Paul D. Sampson, Roman A. Jandarov","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ME","submitted_at":"2015-09-03T17:28:45Z","title":"A novel principal component analysis for spatially-misaligned multivariate air pollution data"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1509.01171","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:a84795a4a0fb30689254aff5bf18f528cbd3b6c53be190457fb01e516f04dd89","target":"record","created_at":"2026-05-18T01:34:04Z","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":"c6ac3bcf87d2180e6b50d406a1a4ff5c137b1b6e17819d07e71454412c55012a","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ME","submitted_at":"2015-09-03T17:28:45Z","title_canon_sha256":"d6f5aee02f6ad5a2925fb150fb97ee3299597bb288252a478d884364b06afeed"},"schema_version":"1.0","source":{"id":"1509.01171","kind":"arxiv","version":1}},"canonical_sha256":"5c310e874515c0bbbbe8f2cb54e44e2e27204221c182e3b6c52004dbcc93f03e","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"5c310e874515c0bbbbe8f2cb54e44e2e27204221c182e3b6c52004dbcc93f03e","first_computed_at":"2026-05-18T01:34:04.171304Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T01:34:04.171304Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"bdirrBh22wIt76QJJaHK2pL8m0TUovOLhU8D1fQJEsDx8QEg0wft9bIO32upwPiSUCQzFeBxuhJEy6jHTQTLDQ==","signature_status":"signed_v1","signed_at":"2026-05-18T01:34:04.171913Z","signed_message":"canonical_sha256_bytes"},"source_id":"1509.01171","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:a84795a4a0fb30689254aff5bf18f528cbd3b6c53be190457fb01e516f04dd89","sha256:1c5627e1c084023d97e276fd3efac45a5b01ff245b4d731208f54fd1b64be98b"],"state_sha256":"774eab83c0791849fc1a9267a2b1ed1bd319b5055234b4abaf50444640edcb70"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"g4ArAwxriB7Bqfx1Gsq2n26RLIJVziSRgnxfdWndJMMhA5QP5qBvrm7UdPSVZURqCx7EX+GD4d9Dx55s+g31Bg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-07T23:25:12.029147Z","bundle_sha256":"4eb0bf63a59bb75e57069c94ec1610cc235bb242f22426f9e48f5af3e5de7672"}}