{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:EC3G3UDMULTVTUS25TCJV5IPGM","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":"9304e8e5628af071eb889c46004c4e20bc26c114b198bfe1d909d97d73394d67","cross_cats_sorted":["astro-ph.IM","astro-ph.SR"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"astro-ph.EP","submitted_at":"2022-04-29T20:22:42Z","title_canon_sha256":"c0557f505fc590e2bfc738b7793046a844ad03cf9e554f79725888876c2dd4bf"},"schema_version":"1.0","source":{"id":"2205.00067","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2205.00067","created_at":"2026-07-05T04:43:45Z"},{"alias_kind":"arxiv_version","alias_value":"2205.00067v1","created_at":"2026-07-05T04:43:45Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2205.00067","created_at":"2026-07-05T04:43:45Z"},{"alias_kind":"pith_short_12","alias_value":"EC3G3UDMULTV","created_at":"2026-07-05T04:43:45Z"},{"alias_kind":"pith_short_16","alias_value":"EC3G3UDMULTVTUS2","created_at":"2026-07-05T04:43:45Z"},{"alias_kind":"pith_short_8","alias_value":"EC3G3UDM","created_at":"2026-07-05T04:43:45Z"}],"graph_snapshots":[{"event_id":"sha256:af90455c07f2339357ecbec0fef06d11875e9417ce04646b818a00c635706b39","target":"graph","created_at":"2026-07-05T04:43:45Z","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"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2205.00067/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"The detection and characterization of an increasing variety of exoplanets has been in part possible thanks to the continuous development of high-resolution, stable spectrographs, and using the Doppler radial-velocity (RV) method. The Cross Correlation Function (CCF) method is one of the traditional approaches for RV extraction. More recently, template matching was introduced as an advantageous alternative for M-dwarf stars. In this paper, we describe a new implementation of template matching within a semi-Bayesian framework, providing a more statistically principled characterization of the RV ","authors_text":"A. Cabral, A. Mehner, A. M. Silva, A. Sozzetti, A. Su\\'arez Mascare\\~no, C. J.A.P. Martins, C. Lovis, D. Ehrenreich, D. M\\'egevand, E. Palle, F. Pepe, G. Lo Curto, H. M. Tabernero, J. H. C. Martins, J. I. Gonz\\'alez Hern\\'andez, J. Lillo-Box, J. P. Faria, M. R. Zapatero Osorio, N. C. Hara, N. C. Santos, N. J. Nunes, P. Di Marcantonio, P. Figueira, P. T. P. Viana, R. Allart, R. Rebolo, S. Cristiani, S. G. Sousa, S. Udry, V. Adibekyan, X. Dumusque","cross_cats":["astro-ph.IM","astro-ph.SR"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"astro-ph.EP","submitted_at":"2022-04-29T20:22:42Z","title":"A novel framework for semi-Bayesian radial velocities through template matching"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2205.00067","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:d8bc736996a8229fabcf2eed40434acda3d715de20944dbfe7e351fcdb2d909c","target":"record","created_at":"2026-07-05T04:43:45Z","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":"9304e8e5628af071eb889c46004c4e20bc26c114b198bfe1d909d97d73394d67","cross_cats_sorted":["astro-ph.IM","astro-ph.SR"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"astro-ph.EP","submitted_at":"2022-04-29T20:22:42Z","title_canon_sha256":"c0557f505fc590e2bfc738b7793046a844ad03cf9e554f79725888876c2dd4bf"},"schema_version":"1.0","source":{"id":"2205.00067","kind":"arxiv","version":1}},"canonical_sha256":"20b66dd06ca2e759d25aecc49af50f331935236ff2004bd67d8f0ad1b6e51469","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"20b66dd06ca2e759d25aecc49af50f331935236ff2004bd67d8f0ad1b6e51469","first_computed_at":"2026-07-05T04:43:45.107764Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T04:43:45.107764Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"zexpgxCqj1TXz1+DeEgGFMJhwVRqv9mGcxrRD6cqYR9vDFwAWHt6We7hHp45i5NP+xTXZW3UqY9t3sPlyU36AQ==","signature_status":"signed_v1","signed_at":"2026-07-05T04:43:45.108290Z","signed_message":"canonical_sha256_bytes"},"source_id":"2205.00067","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:d8bc736996a8229fabcf2eed40434acda3d715de20944dbfe7e351fcdb2d909c","sha256:af90455c07f2339357ecbec0fef06d11875e9417ce04646b818a00c635706b39"],"state_sha256":"a7bbc1cebeda855641bc235c4c942db3236209e07590cf238d387d63e1521b5f"}