{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2013:J526AZPDSP5D2MXF44SNJFE22M","short_pith_number":"pith:J526AZPD","schema_version":"1.0","canonical_sha256":"4f75e065e393fa3d32e5e724d4949ad326315404420cab7f771cf600c4a0dc9e","source":{"kind":"arxiv","id":"1308.3644","version":1},"attestation_state":"computed","paper":{"title":"Astrophysically robust systematics removal using variational inference: application to the first month of Kepler data","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"astro-ph.IM","authors_text":"A. McQuillan, S. Aigrain, S. Reece, S. Roberts","submitted_at":"2013-08-16T14:46:21Z","abstract_excerpt":"Space-based transit search missions such as Kepler are collecting large numbers of stellar light curves of unprecedented photometric precision and time coverage. However, before this scientific goldmine can be exploited fully, the data must be cleaned of instrumental artefacts. We present a new method to correct common-mode systematics in large ensembles of very high precision light curves. It is based on a Bayesian linear basis model and uses shrinkage priors for robustness, variational inference for speed, and a de-noising step based on empirical mode decomposition to prevent the introductio"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"1308.3644","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"astro-ph.IM","submitted_at":"2013-08-16T14:46:21Z","cross_cats_sorted":[],"title_canon_sha256":"be8f2e18d755430393a4c2d75ad9ccaa5bbfeeab3b5a5f2ea9826528a862b750","abstract_canon_sha256":"8c66f8fa67c9cc196668d5676cd218b8a59501cdabda33bd7fecfc91b72e4314"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T01:48:14.623108Z","signature_b64":"/IIu/RC4VCb1EY5coizPkPka9VPCVUVzPdLMJ4XJ/PEFdAqs+wkShst9Ox5osfLiCR6wNTzgM98BgwkNQ2/UDQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"4f75e065e393fa3d32e5e724d4949ad326315404420cab7f771cf600c4a0dc9e","last_reissued_at":"2026-05-18T01:48:14.622527Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T01:48:14.622527Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Astrophysically robust systematics removal using variational inference: application to the first month of Kepler data","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"astro-ph.IM","authors_text":"A. McQuillan, S. Aigrain, S. Reece, S. Roberts","submitted_at":"2013-08-16T14:46:21Z","abstract_excerpt":"Space-based transit search missions such as Kepler are collecting large numbers of stellar light curves of unprecedented photometric precision and time coverage. However, before this scientific goldmine can be exploited fully, the data must be cleaned of instrumental artefacts. We present a new method to correct common-mode systematics in large ensembles of very high precision light curves. It is based on a Bayesian linear basis model and uses shrinkage priors for robustness, variational inference for speed, and a de-noising step based on empirical mode decomposition to prevent the introductio"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1308.3644","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"},"aliases":[{"alias_kind":"arxiv","alias_value":"1308.3644","created_at":"2026-05-18T01:48:14.622631+00:00"},{"alias_kind":"arxiv_version","alias_value":"1308.3644v1","created_at":"2026-05-18T01:48:14.622631+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1308.3644","created_at":"2026-05-18T01:48:14.622631+00:00"},{"alias_kind":"pith_short_12","alias_value":"J526AZPDSP5D","created_at":"2026-05-18T12:27:49.015174+00:00"},{"alias_kind":"pith_short_16","alias_value":"J526AZPDSP5D2MXF","created_at":"2026-05-18T12:27:49.015174+00:00"},{"alias_kind":"pith_short_8","alias_value":"J526AZPD","created_at":"2026-05-18T12:27:49.015174+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/J526AZPDSP5D2MXF44SNJFE22M","json":"https://pith.science/pith/J526AZPDSP5D2MXF44SNJFE22M.json","graph_json":"https://pith.science/api/pith-number/J526AZPDSP5D2MXF44SNJFE22M/graph.json","events_json":"https://pith.science/api/pith-number/J526AZPDSP5D2MXF44SNJFE22M/events.json","paper":"https://pith.science/paper/J526AZPD"},"agent_actions":{"view_html":"https://pith.science/pith/J526AZPDSP5D2MXF44SNJFE22M","download_json":"https://pith.science/pith/J526AZPDSP5D2MXF44SNJFE22M.json","view_paper":"https://pith.science/paper/J526AZPD","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1308.3644&json=true","fetch_graph":"https://pith.science/api/pith-number/J526AZPDSP5D2MXF44SNJFE22M/graph.json","fetch_events":"https://pith.science/api/pith-number/J526AZPDSP5D2MXF44SNJFE22M/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/J526AZPDSP5D2MXF44SNJFE22M/action/timestamp_anchor","attest_storage":"https://pith.science/pith/J526AZPDSP5D2MXF44SNJFE22M/action/storage_attestation","attest_author":"https://pith.science/pith/J526AZPDSP5D2MXF44SNJFE22M/action/author_attestation","sign_citation":"https://pith.science/pith/J526AZPDSP5D2MXF44SNJFE22M/action/citation_signature","submit_replication":"https://pith.science/pith/J526AZPDSP5D2MXF44SNJFE22M/action/replication_record"}},"created_at":"2026-05-18T01:48:14.622631+00:00","updated_at":"2026-05-18T01:48:14.622631+00:00"}