{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2021:B52X7GJ6XBMAZWS3BU5CVCEBSR","short_pith_number":"pith:B52X7GJ6","canonical_record":{"source":{"id":"2102.09892","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"astro-ph.IM","submitted_at":"2021-02-19T12:20:49Z","cross_cats_sorted":["astro-ph.HE"],"title_canon_sha256":"03eade8ccb1adfef6336b961e921f0648c48706cc61344de8076336ede944226","abstract_canon_sha256":"b8d2eeb5c16ef258b3a5dfe452fb068c8e7f97f001075abd0e137eafc4631bfe"},"schema_version":"1.0"},"canonical_sha256":"0f757f993eb8580cda5b0d3a2a8881947b8eb89c22414d96ef9cfc0f036efe8c","source":{"kind":"arxiv","id":"2102.09892","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2102.09892","created_at":"2026-07-05T02:25:39Z"},{"alias_kind":"arxiv_version","alias_value":"2102.09892v1","created_at":"2026-07-05T02:25:39Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2102.09892","created_at":"2026-07-05T02:25:39Z"},{"alias_kind":"pith_short_12","alias_value":"B52X7GJ6XBMA","created_at":"2026-07-05T02:25:39Z"},{"alias_kind":"pith_short_16","alias_value":"B52X7GJ6XBMAZWS3","created_at":"2026-07-05T02:25:39Z"},{"alias_kind":"pith_short_8","alias_value":"B52X7GJ6","created_at":"2026-07-05T02:25:39Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2021:B52X7GJ6XBMAZWS3BU5CVCEBSR","target":"record","payload":{"canonical_record":{"source":{"id":"2102.09892","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"astro-ph.IM","submitted_at":"2021-02-19T12:20:49Z","cross_cats_sorted":["astro-ph.HE"],"title_canon_sha256":"03eade8ccb1adfef6336b961e921f0648c48706cc61344de8076336ede944226","abstract_canon_sha256":"b8d2eeb5c16ef258b3a5dfe452fb068c8e7f97f001075abd0e137eafc4631bfe"},"schema_version":"1.0"},"canonical_sha256":"0f757f993eb8580cda5b0d3a2a8881947b8eb89c22414d96ef9cfc0f036efe8c","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T02:25:39.190463Z","signature_b64":"MZocWHiZGw+kt7AKqydSGn8hUXgsQYmmTt4e+gSs3bRvDUSQ7nAHZ5K6TeT1nL2NjjxFB3PNGCm1T89hzwt0AQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"0f757f993eb8580cda5b0d3a2a8881947b8eb89c22414d96ef9cfc0f036efe8c","last_reissued_at":"2026-07-05T02:25:39.189967Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T02:25:39.189967Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2102.09892","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":"2026-07-05T02:25:39Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"2N4ftg262ZxjPUfNlVmdPgUa5GIBzceKepzPNi1QS6YokLurzUy1rR9eIs9uHsqURKvwkkfiqtU5ZdwqmzFEAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-05T15:03:11.448997Z"},"content_sha256":"209b1191a0d42c2fb627be03d746aefda50a2b77aadc9cebc76c769abb24bdde","schema_version":"1.0","event_id":"sha256:209b1191a0d42c2fb627be03d746aefda50a2b77aadc9cebc76c769abb24bdde"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2021:B52X7GJ6XBMAZWS3BU5CVCEBSR","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Transient-optimised real-bogus classification with Bayesian Convolutional Neural Networks -- sifting the GOTO candidate stream","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["astro-ph.HE"],"primary_cat":"astro-ph.IM","authors_text":"A. Chrimes, A. Levan, B. Gompertz, C. Duffy, D. K. Galloway, D. Mata S\\'anchez, D. Mkrtichian, D. Pollacco, D. Steeghs, E. Daw, E. Pall\\'e, E. Rol, E. Stanway, E. Thrane, G. Ramsay, J. Lyman, J. Maund, J. McCormac, J. Mullaney, K. Ackley, K. Ulaczyk, K. Wiersema, L. K. Nuttall, L. Makrygianni, M. J. Dyer, M. R. Kennedy, P. A. Str{\\o}m, P. Chote, P. Irawati, P. O'Brien, R. Cutter, R. Eyles-Ferris, R. Kotak, R. P. Breton, R. Starling, S. Aukkaravittayapun, S. Awiphan, S. C. Williams, S. Littlefair, S. Mattila, S. Poshyachinda, S. Tooke, T. Heikkil\\\"a, T. L. Killestein, U. Burhanudin, U. Sawangwit, V. Dhillon, Y.-L. Mong","submitted_at":"2021-02-19T12:20:49Z","abstract_excerpt":"Large-scale sky surveys have played a transformative role in our understanding of astrophysical transients, only made possible by increasingly powerful machine learning-based filtering to accurately sift through the vast quantities of incoming data generated. In this paper, we present a new real-bogus classifier based on a Bayesian convolutional neural network that provides nuanced, uncertainty-aware classification of transient candidates in difference imaging, and demonstrate its application to the datastream from the GOTO wide-field optical survey. Not only are candidates assigned a well-cal"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2102.09892","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":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2102.09892/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"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":"2026-07-05T02:25:39Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"80Zi/lLVdaOmRje6lfgueofKF1Tg3RQ4SvPuqXex5AHc7JlpvN+Aq7Kx9Br86EKFsSqghB3GiIlC3K2yVYGSDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-05T15:03:11.449651Z"},"content_sha256":"b3acb920758dfff0410a8844ff7e38256c6920993c4ddac7681ed3a30c1d9beb","schema_version":"1.0","event_id":"sha256:b3acb920758dfff0410a8844ff7e38256c6920993c4ddac7681ed3a30c1d9beb"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/B52X7GJ6XBMAZWS3BU5CVCEBSR/bundle.json","state_url":"https://pith.science/pith/B52X7GJ6XBMAZWS3BU5CVCEBSR/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/B52X7GJ6XBMAZWS3BU5CVCEBSR/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":"2026-07-05T15:03:11Z","links":{"resolver":"https://pith.science/pith/B52X7GJ6XBMAZWS3BU5CVCEBSR","bundle":"https://pith.science/pith/B52X7GJ6XBMAZWS3BU5CVCEBSR/bundle.json","state":"https://pith.science/pith/B52X7GJ6XBMAZWS3BU5CVCEBSR/state.json","well_known_bundle":"https://pith.science/.well-known/pith/B52X7GJ6XBMAZWS3BU5CVCEBSR/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2021:B52X7GJ6XBMAZWS3BU5CVCEBSR","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":"b8d2eeb5c16ef258b3a5dfe452fb068c8e7f97f001075abd0e137eafc4631bfe","cross_cats_sorted":["astro-ph.HE"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"astro-ph.IM","submitted_at":"2021-02-19T12:20:49Z","title_canon_sha256":"03eade8ccb1adfef6336b961e921f0648c48706cc61344de8076336ede944226"},"schema_version":"1.0","source":{"id":"2102.09892","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2102.09892","created_at":"2026-07-05T02:25:39Z"},{"alias_kind":"arxiv_version","alias_value":"2102.09892v1","created_at":"2026-07-05T02:25:39Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2102.09892","created_at":"2026-07-05T02:25:39Z"},{"alias_kind":"pith_short_12","alias_value":"B52X7GJ6XBMA","created_at":"2026-07-05T02:25:39Z"},{"alias_kind":"pith_short_16","alias_value":"B52X7GJ6XBMAZWS3","created_at":"2026-07-05T02:25:39Z"},{"alias_kind":"pith_short_8","alias_value":"B52X7GJ6","created_at":"2026-07-05T02:25:39Z"}],"graph_snapshots":[{"event_id":"sha256:b3acb920758dfff0410a8844ff7e38256c6920993c4ddac7681ed3a30c1d9beb","target":"graph","created_at":"2026-07-05T02:25:39Z","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/2102.09892/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Large-scale sky surveys have played a transformative role in our understanding of astrophysical transients, only made possible by increasingly powerful machine learning-based filtering to accurately sift through the vast quantities of incoming data generated. In this paper, we present a new real-bogus classifier based on a Bayesian convolutional neural network that provides nuanced, uncertainty-aware classification of transient candidates in difference imaging, and demonstrate its application to the datastream from the GOTO wide-field optical survey. Not only are candidates assigned a well-cal","authors_text":"A. Chrimes, A. Levan, B. Gompertz, C. Duffy, D. K. Galloway, D. Mata S\\'anchez, D. Mkrtichian, D. Pollacco, D. Steeghs, E. Daw, E. Pall\\'e, E. Rol, E. Stanway, E. Thrane, G. Ramsay, J. Lyman, J. Maund, J. McCormac, J. Mullaney, K. Ackley, K. Ulaczyk, K. Wiersema, L. K. Nuttall, L. Makrygianni, M. J. Dyer, M. R. Kennedy, P. A. Str{\\o}m, P. Chote, P. Irawati, P. O'Brien, R. Cutter, R. Eyles-Ferris, R. Kotak, R. P. Breton, R. Starling, S. Aukkaravittayapun, S. Awiphan, S. C. Williams, S. Littlefair, S. Mattila, S. Poshyachinda, S. Tooke, T. Heikkil\\\"a, T. L. Killestein, U. Burhanudin, U. Sawangwit, V. Dhillon, Y.-L. Mong","cross_cats":["astro-ph.HE"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"astro-ph.IM","submitted_at":"2021-02-19T12:20:49Z","title":"Transient-optimised real-bogus classification with Bayesian Convolutional Neural Networks -- sifting the GOTO candidate stream"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2102.09892","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":"sha256:209b1191a0d42c2fb627be03d746aefda50a2b77aadc9cebc76c769abb24bdde","target":"record","created_at":"2026-07-05T02:25:39Z","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":"b8d2eeb5c16ef258b3a5dfe452fb068c8e7f97f001075abd0e137eafc4631bfe","cross_cats_sorted":["astro-ph.HE"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"astro-ph.IM","submitted_at":"2021-02-19T12:20:49Z","title_canon_sha256":"03eade8ccb1adfef6336b961e921f0648c48706cc61344de8076336ede944226"},"schema_version":"1.0","source":{"id":"2102.09892","kind":"arxiv","version":1}},"canonical_sha256":"0f757f993eb8580cda5b0d3a2a8881947b8eb89c22414d96ef9cfc0f036efe8c","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"0f757f993eb8580cda5b0d3a2a8881947b8eb89c22414d96ef9cfc0f036efe8c","first_computed_at":"2026-07-05T02:25:39.189967Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T02:25:39.189967Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"MZocWHiZGw+kt7AKqydSGn8hUXgsQYmmTt4e+gSs3bRvDUSQ7nAHZ5K6TeT1nL2NjjxFB3PNGCm1T89hzwt0AQ==","signature_status":"signed_v1","signed_at":"2026-07-05T02:25:39.190463Z","signed_message":"canonical_sha256_bytes"},"source_id":"2102.09892","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:209b1191a0d42c2fb627be03d746aefda50a2b77aadc9cebc76c769abb24bdde","sha256:b3acb920758dfff0410a8844ff7e38256c6920993c4ddac7681ed3a30c1d9beb"],"state_sha256":"b8890417ed9ee17ed0c3d1d01041d677087cc030ae19d35cd78dfee925457301"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"/VxDVzz8onHiVbG0czXx3wpJjvEWp3VUPq5M7HxKR+icku3IvwYJrOYWR8wkL0thG5XmjdjhweyQqN5XzoQLCw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-05T15:03:11.452604Z","bundle_sha256":"b0067a641dd7db9a361d6fba6d90879fa71ed6aa19800f65159aba5f9ed360cf"}}