{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:DX5I6BW6ZO7UTPIJ5ZVNCDUHC3","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":"aa897726471a0a1d7b92e5dec426c504ed7f013fe69869f7a92c4dd0c7f566d3","cross_cats_sorted":["math.ST","stat.CO","stat.TH"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"stat.ME","submitted_at":"2026-06-23T09:46:18Z","title_canon_sha256":"095b7d7341c758001d1ab35feb59aac50b9788e6bb1a6df65d049c98bb79f5aa"},"schema_version":"1.0","source":{"id":"2606.24357","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2606.24357","created_at":"2026-06-24T01:15:28Z"},{"alias_kind":"arxiv_version","alias_value":"2606.24357v1","created_at":"2026-06-24T01:15:28Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.24357","created_at":"2026-06-24T01:15:28Z"},{"alias_kind":"pith_short_12","alias_value":"DX5I6BW6ZO7U","created_at":"2026-06-24T01:15:28Z"},{"alias_kind":"pith_short_16","alias_value":"DX5I6BW6ZO7UTPIJ","created_at":"2026-06-24T01:15:28Z"},{"alias_kind":"pith_short_8","alias_value":"DX5I6BW6","created_at":"2026-06-24T01:15:28Z"}],"graph_snapshots":[{"event_id":"sha256:e879a06344dcfeb146cf83dc13a5478275794790fee6c170839d52ba65db03e0","target":"graph","created_at":"2026-06-24T01:15:28Z","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/2606.24357/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Covariate selection in Generalized Linear Models (GLMs) is a fundamental problem in statistics, as including irrelevant predictors might lead to overfitting and poor interpretability, while omitting relevant ones might result in biased estimates. Most Bayesian approaches to variable selection -- including spike-and-slab priors and continuous shrinkage priors -- have key limitations, e.g., (i) are based on non fully conjugate formulations, (ii) are restricted to a linear model, or (iii) lack posterior consistency guarantees for the variable selection procedure and model parameters. In this work","authors_text":"Claudio Agostinelli, I\\~nigo Urteaga, Lucia Filippozzi","cross_cats":["math.ST","stat.CO","stat.TH"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"stat.ME","submitted_at":"2026-06-23T09:46:18Z","title":"Bayesian Variable Selection in Generalized Linear Models"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.24357","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":"sha256:3b706a37362e292793a441b197e7b7975a6d987689bda31a7b6cbbe392d8019a","target":"record","created_at":"2026-06-24T01:15:28Z","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":"aa897726471a0a1d7b92e5dec426c504ed7f013fe69869f7a92c4dd0c7f566d3","cross_cats_sorted":["math.ST","stat.CO","stat.TH"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"stat.ME","submitted_at":"2026-06-23T09:46:18Z","title_canon_sha256":"095b7d7341c758001d1ab35feb59aac50b9788e6bb1a6df65d049c98bb79f5aa"},"schema_version":"1.0","source":{"id":"2606.24357","kind":"arxiv","version":1}},"canonical_sha256":"1dfa8f06decbbf49bd09ee6ad10e8716c1d12f115e5771550c94a28a4d15ed08","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"1dfa8f06decbbf49bd09ee6ad10e8716c1d12f115e5771550c94a28a4d15ed08","first_computed_at":"2026-06-24T01:15:28.403393Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-06-24T01:15:28.403393Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"RWUZjdLe/EK70Ve9teTgjzc1YbHy4dYnTT5ibEvSzH80aKZRz4V+oZBgnmaDnCO+6Sm9XLHBpDIhIulztM4qDA==","signature_status":"signed_v1","signed_at":"2026-06-24T01:15:28.403779Z","signed_message":"canonical_sha256_bytes"},"source_id":"2606.24357","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:3b706a37362e292793a441b197e7b7975a6d987689bda31a7b6cbbe392d8019a","sha256:e879a06344dcfeb146cf83dc13a5478275794790fee6c170839d52ba65db03e0"],"state_sha256":"6762bbb053a070b7cf1362edf75f76ea3c9b2647ba74daa68d1c6050ebdb38ab"}