{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:VZNOS3TFXFGGIWTWMTRKWN2WW7","short_pith_number":"pith:VZNOS3TF","canonical_record":{"source":{"id":"2505.11351","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ME","submitted_at":"2025-05-16T15:15:02Z","cross_cats_sorted":[],"title_canon_sha256":"38dc3d77ab7396d05e9d6aaf695ebf99dacf43c007159eb2f07dd6fb5ad6b7fe","abstract_canon_sha256":"c41018b13d9faf5d41ba60f147c275124e039c6ef23f7389a198cf2b5d9da0f6"},"schema_version":"1.0"},"canonical_sha256":"ae5ae96e65b94c645a7664e2ab3756b7c7e49ab718ffd011800f58cd5d3d6d12","source":{"kind":"arxiv","id":"2505.11351","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2505.11351","created_at":"2026-07-05T11:04:14Z"},{"alias_kind":"arxiv_version","alias_value":"2505.11351v1","created_at":"2026-07-05T11:04:14Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2505.11351","created_at":"2026-07-05T11:04:14Z"},{"alias_kind":"pith_short_12","alias_value":"VZNOS3TFXFGG","created_at":"2026-07-05T11:04:14Z"},{"alias_kind":"pith_short_16","alias_value":"VZNOS3TFXFGGIWTW","created_at":"2026-07-05T11:04:14Z"},{"alias_kind":"pith_short_8","alias_value":"VZNOS3TF","created_at":"2026-07-05T11:04:14Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:VZNOS3TFXFGGIWTWMTRKWN2WW7","target":"record","payload":{"canonical_record":{"source":{"id":"2505.11351","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ME","submitted_at":"2025-05-16T15:15:02Z","cross_cats_sorted":[],"title_canon_sha256":"38dc3d77ab7396d05e9d6aaf695ebf99dacf43c007159eb2f07dd6fb5ad6b7fe","abstract_canon_sha256":"c41018b13d9faf5d41ba60f147c275124e039c6ef23f7389a198cf2b5d9da0f6"},"schema_version":"1.0"},"canonical_sha256":"ae5ae96e65b94c645a7664e2ab3756b7c7e49ab718ffd011800f58cd5d3d6d12","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:04:14.783012Z","signature_b64":"kr8UBkOWGnZ1gGXUpuoTRCfpsSxBO3+doldpU3ZbfYtn46kprotL2VP0H4MRcDkG7arsuBM9U+7g1WGFbawPCA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"ae5ae96e65b94c645a7664e2ab3756b7c7e49ab718ffd011800f58cd5d3d6d12","last_reissued_at":"2026-07-05T11:04:14.782570Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:04:14.782570Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2505.11351","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":"2026-07-05T11:04:14Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"T1AeaYDNhJ79m7fWpuxWFtv67rAOIkcXY3oJ7N38y+NYYi5bAo9ZP54Vd+TpmEm0XJqtG4084xDvuYBFiOUHDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-07T07:14:41.829261Z"},"content_sha256":"1b8fcd861bf909ef24142b1a52d1b38d749fa53470b92cc29bed5f594d9bb856","schema_version":"1.0","event_id":"sha256:1b8fcd861bf909ef24142b1a52d1b38d749fa53470b92cc29bed5f594d9bb856"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:VZNOS3TFXFGGIWTWMTRKWN2WW7","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Targeted empirical Bayes for more supervised joint factor analysis","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"stat.ME","authors_text":"David B. Dunson, Glenn Palmer","submitted_at":"2025-05-16T15:15:02Z","abstract_excerpt":"Joint Bayesian factor models are popular for characterizing relationships between multivariate correlated predictors and a response variable. Standard models assume that all variables, including both the predictors and the response, are conditionally independent given latent factors. In marginalizing out these factors, one obtains a low rank plus diagonal factorization for the joint covariance, which implies a linear regression for the response given the predictors. Although there are many desirable properties of such models, these methods can struggle to identify the signal when the response "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2505.11351","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/2505.11351/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":"2026-07-05T11:04:14Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"l0S+ElDAhKzQeuPu3Y8NTQ1NUB9TamX6LBdOKtqN9U/R5D1ovxg6o2WLTakUZsTbVYVHJbNhM7uOvwVK+svoDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-07T07:14:41.829918Z"},"content_sha256":"18f475d84e45369d3be2f934fee67c841b2aff7572b5b8ec28669368d60fadec","schema_version":"1.0","event_id":"sha256:18f475d84e45369d3be2f934fee67c841b2aff7572b5b8ec28669368d60fadec"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/VZNOS3TFXFGGIWTWMTRKWN2WW7/bundle.json","state_url":"https://pith.science/pith/VZNOS3TFXFGGIWTWMTRKWN2WW7/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/VZNOS3TFXFGGIWTWMTRKWN2WW7/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":"2026-07-07T07:14:41Z","links":{"resolver":"https://pith.science/pith/VZNOS3TFXFGGIWTWMTRKWN2WW7","bundle":"https://pith.science/pith/VZNOS3TFXFGGIWTWMTRKWN2WW7/bundle.json","state":"https://pith.science/pith/VZNOS3TFXFGGIWTWMTRKWN2WW7/state.json","well_known_bundle":"https://pith.science/.well-known/pith/VZNOS3TFXFGGIWTWMTRKWN2WW7/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:VZNOS3TFXFGGIWTWMTRKWN2WW7","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":"c41018b13d9faf5d41ba60f147c275124e039c6ef23f7389a198cf2b5d9da0f6","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ME","submitted_at":"2025-05-16T15:15:02Z","title_canon_sha256":"38dc3d77ab7396d05e9d6aaf695ebf99dacf43c007159eb2f07dd6fb5ad6b7fe"},"schema_version":"1.0","source":{"id":"2505.11351","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2505.11351","created_at":"2026-07-05T11:04:14Z"},{"alias_kind":"arxiv_version","alias_value":"2505.11351v1","created_at":"2026-07-05T11:04:14Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2505.11351","created_at":"2026-07-05T11:04:14Z"},{"alias_kind":"pith_short_12","alias_value":"VZNOS3TFXFGG","created_at":"2026-07-05T11:04:14Z"},{"alias_kind":"pith_short_16","alias_value":"VZNOS3TFXFGGIWTW","created_at":"2026-07-05T11:04:14Z"},{"alias_kind":"pith_short_8","alias_value":"VZNOS3TF","created_at":"2026-07-05T11:04:14Z"}],"graph_snapshots":[{"event_id":"sha256:18f475d84e45369d3be2f934fee67c841b2aff7572b5b8ec28669368d60fadec","target":"graph","created_at":"2026-07-05T11:04:14Z","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/2505.11351/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Joint Bayesian factor models are popular for characterizing relationships between multivariate correlated predictors and a response variable. Standard models assume that all variables, including both the predictors and the response, are conditionally independent given latent factors. In marginalizing out these factors, one obtains a low rank plus diagonal factorization for the joint covariance, which implies a linear regression for the response given the predictors. Although there are many desirable properties of such models, these methods can struggle to identify the signal when the response ","authors_text":"David B. Dunson, Glenn Palmer","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ME","submitted_at":"2025-05-16T15:15:02Z","title":"Targeted empirical Bayes for more supervised joint factor analysis"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2505.11351","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":"sha256:1b8fcd861bf909ef24142b1a52d1b38d749fa53470b92cc29bed5f594d9bb856","target":"record","created_at":"2026-07-05T11:04:14Z","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":"c41018b13d9faf5d41ba60f147c275124e039c6ef23f7389a198cf2b5d9da0f6","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ME","submitted_at":"2025-05-16T15:15:02Z","title_canon_sha256":"38dc3d77ab7396d05e9d6aaf695ebf99dacf43c007159eb2f07dd6fb5ad6b7fe"},"schema_version":"1.0","source":{"id":"2505.11351","kind":"arxiv","version":1}},"canonical_sha256":"ae5ae96e65b94c645a7664e2ab3756b7c7e49ab718ffd011800f58cd5d3d6d12","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"ae5ae96e65b94c645a7664e2ab3756b7c7e49ab718ffd011800f58cd5d3d6d12","first_computed_at":"2026-07-05T11:04:14.782570Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:04:14.782570Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"kr8UBkOWGnZ1gGXUpuoTRCfpsSxBO3+doldpU3ZbfYtn46kprotL2VP0H4MRcDkG7arsuBM9U+7g1WGFbawPCA==","signature_status":"signed_v1","signed_at":"2026-07-05T11:04:14.783012Z","signed_message":"canonical_sha256_bytes"},"source_id":"2505.11351","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:1b8fcd861bf909ef24142b1a52d1b38d749fa53470b92cc29bed5f594d9bb856","sha256:18f475d84e45369d3be2f934fee67c841b2aff7572b5b8ec28669368d60fadec"],"state_sha256":"355412c25b84b0fb989596de875e74fdcefb184c8729f6957a23e1b9f7b975a6"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"aFOofSFjr/Qj0x48UPouZce+XGiETwcwPx7xo5wrDraKEXavxddaIXyT82+fGRcCqCVNbTTQ+2V5go8IcUfPBQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-07T07:14:41.834643Z","bundle_sha256":"c68707846ba61978308eebb2aa8364a8c2484f73aae105909835dbb1ab0a72fc"}}