{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2015:HG67FYGDF3QIY2EZ5Q4AWVHRDW","short_pith_number":"pith:HG67FYGD","canonical_record":{"source":{"id":"1503.05628","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"q-bio.QM","submitted_at":"2015-01-12T02:16:01Z","cross_cats_sorted":["q-bio.PE"],"title_canon_sha256":"99427633f7f665c0ceaf64215fc0297ca141e06a873bbd73e11f7c0d7252f5b9","abstract_canon_sha256":"50862d89ac48475fdc3309977eeef3acbc0e0e279e4cf8c868b55ce42970b1ae"},"schema_version":"1.0"},"canonical_sha256":"39bdf2e0c32ee08c6899ec380b54f11db44ab4bab6df536c45068604495f9601","source":{"kind":"arxiv","id":"1503.05628","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1503.05628","created_at":"2026-05-18T02:20:58Z"},{"alias_kind":"arxiv_version","alias_value":"1503.05628v1","created_at":"2026-05-18T02:20:58Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1503.05628","created_at":"2026-05-18T02:20:58Z"},{"alias_kind":"pith_short_12","alias_value":"HG67FYGDF3QI","created_at":"2026-05-18T12:29:25Z"},{"alias_kind":"pith_short_16","alias_value":"HG67FYGDF3QIY2EZ","created_at":"2026-05-18T12:29:25Z"},{"alias_kind":"pith_short_8","alias_value":"HG67FYGD","created_at":"2026-05-18T12:29:25Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2015:HG67FYGDF3QIY2EZ5Q4AWVHRDW","target":"record","payload":{"canonical_record":{"source":{"id":"1503.05628","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"q-bio.QM","submitted_at":"2015-01-12T02:16:01Z","cross_cats_sorted":["q-bio.PE"],"title_canon_sha256":"99427633f7f665c0ceaf64215fc0297ca141e06a873bbd73e11f7c0d7252f5b9","abstract_canon_sha256":"50862d89ac48475fdc3309977eeef3acbc0e0e279e4cf8c868b55ce42970b1ae"},"schema_version":"1.0"},"canonical_sha256":"39bdf2e0c32ee08c6899ec380b54f11db44ab4bab6df536c45068604495f9601","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T02:20:58.549543Z","signature_b64":"Viv9FjI+Q4EOQi+njcSv4SAwWeG42QDZJgTF+92zBbVSCS0BsqKzkU/aaOxRPcoSb5CL/VnO922ru6MK/I4qCQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"39bdf2e0c32ee08c6899ec380b54f11db44ab4bab6df536c45068604495f9601","last_reissued_at":"2026-05-18T02:20:58.548886Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T02:20:58.548886Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1503.05628","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":"2026-05-18T02:20:58Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"bYHr0pfm2TgBzPREVMrypB6eCzG4k/KN7P/wXqGxu+G2639HBav2ylvMuMrUuOr6JFLYDpl5r1TJQUVDr+5xCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-03T04:34:17.097689Z"},"content_sha256":"28388bf906b8ff823f59dc807f2e65a1aa232f6d82f44c0b7e3e4570b8194c3c","schema_version":"1.0","event_id":"sha256:28388bf906b8ff823f59dc807f2e65a1aa232f6d82f44c0b7e3e4570b8194c3c"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2015:HG67FYGDF3QIY2EZ5Q4AWVHRDW","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Accurate Estimation of Quantitative Trait Locus Effects with Epistatic by Improved Variational Linear Regression","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["q-bio.PE"],"primary_cat":"q-bio.QM","authors_text":"Jingzhuo Wang, Zhongming Wang, Zijian Dong","submitted_at":"2015-01-12T02:16:01Z","abstract_excerpt":"Bayesian approaches to variable selection have been widely used for quantitative trait locus (QTL) mapping. The Markov chain Monte Carlo (MCMC) algorithms for that aim are often difficult to be implemented for high-dimensional variable selection problems, such as the ones arising in epistatic analysis. Variational approximation is an alternative to MCMC, and variational linear regression (VLR) is an effective solution for the variable selection problems, but lacks accuracy in some QTL mapping problems where there are many more variables than samples. In this paper, we propose an effective meth"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1503.05628","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":"2026-05-18T02:20:58Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"+fykaROogaFCt8kea8YYV+MB4S8Z5qN9Ac8HJFxazpwMCGvfqvyjhnhcdozAD6oh0jFMbb5eFNlJpaX+nD5eAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-03T04:34:17.098038Z"},"content_sha256":"cc0d4c4e572a490d0e9a69541180a5370b7640400068a82c34b337ecf1d8e16f","schema_version":"1.0","event_id":"sha256:cc0d4c4e572a490d0e9a69541180a5370b7640400068a82c34b337ecf1d8e16f"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/HG67FYGDF3QIY2EZ5Q4AWVHRDW/bundle.json","state_url":"https://pith.science/pith/HG67FYGDF3QIY2EZ5Q4AWVHRDW/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/HG67FYGDF3QIY2EZ5Q4AWVHRDW/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":"2026-07-03T04:34:17Z","links":{"resolver":"https://pith.science/pith/HG67FYGDF3QIY2EZ5Q4AWVHRDW","bundle":"https://pith.science/pith/HG67FYGDF3QIY2EZ5Q4AWVHRDW/bundle.json","state":"https://pith.science/pith/HG67FYGDF3QIY2EZ5Q4AWVHRDW/state.json","well_known_bundle":"https://pith.science/.well-known/pith/HG67FYGDF3QIY2EZ5Q4AWVHRDW/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2015:HG67FYGDF3QIY2EZ5Q4AWVHRDW","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":"50862d89ac48475fdc3309977eeef3acbc0e0e279e4cf8c868b55ce42970b1ae","cross_cats_sorted":["q-bio.PE"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"q-bio.QM","submitted_at":"2015-01-12T02:16:01Z","title_canon_sha256":"99427633f7f665c0ceaf64215fc0297ca141e06a873bbd73e11f7c0d7252f5b9"},"schema_version":"1.0","source":{"id":"1503.05628","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1503.05628","created_at":"2026-05-18T02:20:58Z"},{"alias_kind":"arxiv_version","alias_value":"1503.05628v1","created_at":"2026-05-18T02:20:58Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1503.05628","created_at":"2026-05-18T02:20:58Z"},{"alias_kind":"pith_short_12","alias_value":"HG67FYGDF3QI","created_at":"2026-05-18T12:29:25Z"},{"alias_kind":"pith_short_16","alias_value":"HG67FYGDF3QIY2EZ","created_at":"2026-05-18T12:29:25Z"},{"alias_kind":"pith_short_8","alias_value":"HG67FYGD","created_at":"2026-05-18T12:29:25Z"}],"graph_snapshots":[{"event_id":"sha256:cc0d4c4e572a490d0e9a69541180a5370b7640400068a82c34b337ecf1d8e16f","target":"graph","created_at":"2026-05-18T02:20:58Z","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":"Bayesian approaches to variable selection have been widely used for quantitative trait locus (QTL) mapping. The Markov chain Monte Carlo (MCMC) algorithms for that aim are often difficult to be implemented for high-dimensional variable selection problems, such as the ones arising in epistatic analysis. Variational approximation is an alternative to MCMC, and variational linear regression (VLR) is an effective solution for the variable selection problems, but lacks accuracy in some QTL mapping problems where there are many more variables than samples. In this paper, we propose an effective meth","authors_text":"Jingzhuo Wang, Zhongming Wang, Zijian Dong","cross_cats":["q-bio.PE"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"q-bio.QM","submitted_at":"2015-01-12T02:16:01Z","title":"Accurate Estimation of Quantitative Trait Locus Effects with Epistatic by Improved Variational Linear Regression"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1503.05628","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":"sha256:28388bf906b8ff823f59dc807f2e65a1aa232f6d82f44c0b7e3e4570b8194c3c","target":"record","created_at":"2026-05-18T02:20:58Z","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":"50862d89ac48475fdc3309977eeef3acbc0e0e279e4cf8c868b55ce42970b1ae","cross_cats_sorted":["q-bio.PE"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"q-bio.QM","submitted_at":"2015-01-12T02:16:01Z","title_canon_sha256":"99427633f7f665c0ceaf64215fc0297ca141e06a873bbd73e11f7c0d7252f5b9"},"schema_version":"1.0","source":{"id":"1503.05628","kind":"arxiv","version":1}},"canonical_sha256":"39bdf2e0c32ee08c6899ec380b54f11db44ab4bab6df536c45068604495f9601","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"39bdf2e0c32ee08c6899ec380b54f11db44ab4bab6df536c45068604495f9601","first_computed_at":"2026-05-18T02:20:58.548886Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T02:20:58.548886Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Viv9FjI+Q4EOQi+njcSv4SAwWeG42QDZJgTF+92zBbVSCS0BsqKzkU/aaOxRPcoSb5CL/VnO922ru6MK/I4qCQ==","signature_status":"signed_v1","signed_at":"2026-05-18T02:20:58.549543Z","signed_message":"canonical_sha256_bytes"},"source_id":"1503.05628","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:28388bf906b8ff823f59dc807f2e65a1aa232f6d82f44c0b7e3e4570b8194c3c","sha256:cc0d4c4e572a490d0e9a69541180a5370b7640400068a82c34b337ecf1d8e16f"],"state_sha256":"81569b055b0ef8b3fc8e9f328d52daab8adefc9917659ac848f7ed8c456b2af7"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"emWFiEmJ2Vx1JXAk/zZgk8Eu1yOSYk1lu8uh0hraNicYQBLDaiyx2h2SBzrIZdz0Ee4iCVP02wzDYlpL4Xi2Bw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-03T04:34:17.100075Z","bundle_sha256":"adc2945b1eaf08bb2ba624b6d95b1d755f0227877b2c9de576c7fa10b7a96bf0"}}