{"as_of":"2026-08-08T22:24:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:3507313313170f787c2a2ab41833d1e4db83a8424d0880cd0f870b7fc2078f05","coverage":[{"denominator":0,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":3,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":3,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-08T06:32:00.761636+00:00","state":"measured"},{"denominator":3,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":3,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T13:20:17.697308Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"pith","source_observed_at":"2026-08-04T22:12:40.624315Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2505.08288","last_updated":"2025-05-13T07:05:27Z","snapshot_observed_at":"2026-08-07T15:47:38.832175Z","submitted_at":"2025-05-13T07:05:27Z","title":"High-dimensional Bayesian Tobit regression for censored response with Horseshoe prior","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2505.08288","snapshot_observed_at":"2026-08-07T13:20:17.697308Z","title":null,"venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2505.22211","last_updated":"2025-05-28T10:39:05Z","snapshot_observed_at":"2026-08-07T13:10:23.570644Z","submitted_at":"2025-05-28T10:39:05Z","title":"Handling bounded response in high dimensions: a Horseshoe prior Bayesian Beta regression approach","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-07T13:20:17.697308Z"},"links":{"cited_paper":"/paper/2505.08288","citing_paper":"/paper/2505.22211"},"observation_digest":"sha256:5dc6e1edbfe9098f852673b8b1056808576f2496133f096c7f16a487aa0ad267","observation_id":"533cfa3d-cafe-43e4-99f5-81ee3ba198df","resolution":{"observed_at":"2026-08-07T13:20:17.697308Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2505.08288","last_updated":"2025-05-13T07:05:27Z","snapshot_observed_at":"2026-08-07T15:47:38.832175Z","submitted_at":"2025-05-13T07:05:27Z","title":"High-dimensional Bayesian Tobit regression for censored response with Horseshoe prior","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2505.08288","snapshot_observed_at":"2026-08-07T05:35:16.321855Z","title":null,"venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2506.07790","last_updated":"2025-06-09T14:13:02Z","snapshot_observed_at":"2026-08-07T05:22:36.976370Z","submitted_at":"2025-06-09T14:13:02Z","title":"Heavy Lasso: sparse penalized regression under heavy-tailed noise via data-augmented soft-thresholding","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-07T05:35:16.321855Z"},"links":{"cited_paper":"/paper/2505.08288","citing_paper":"/paper/2506.07790"},"observation_digest":"sha256:0eae240a0cfd4c1bd2a5762ac74c0bc900093a3d0c7ed523cdbe8c1d6cd3f2e2","observation_id":"6812aedd-0916-46b5-811d-c74c878ab322","resolution":{"observed_at":"2026-08-07T05:35:16.321855Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2505.08288","last_updated":"2025-05-13T07:05:27Z","snapshot_observed_at":"2026-08-07T15:47:38.832175Z","submitted_at":"2025-05-13T07:05:27Z","title":"High-dimensional Bayesian Tobit regression for censored response with Horseshoe prior","version":1},"cited_work":{"arxiv_id":"2505.08288","doi":null,"metadata_source":"pith","pith_arxiv_id":"2505.08288","snapshot_observed_at":"2026-08-04T22:12:40.624315Z","title":"High-dimensional Bayesian Tobit regression for censored response with Horseshoe prior","venue":"stat.ME","work_id":"334cc15a-114b-4b8e-8712-33fdaeb5a11a","year":2025},"citing_paper":{"arxiv_id":"2509.07501","last_updated":"2025-09-09T08:28:21Z","snapshot_observed_at":"2026-08-08T00:57:16.386516Z","submitted_at":"2025-09-09T08:28:21Z","title":"Bayesian Pliable Lasso with Horseshoe Prior for Interaction Effects in GLMs with Missing Responses","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-04T22:12:40.562890Z"},"links":{"cited_paper":"/paper/2505.08288","citing_paper":"/paper/2509.07501"},"observation_digest":"sha256:3af6694848052618ac8cbbd4f00af1b7412b3d6e229d3f05e3920b794a1b3c10","observation_id":"1fd77a38-a521-4be2-bc0c-44d87a830b82","resolution":{"observed_at":"2026-08-04T22:12:40.630348Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2505.08288/citation-record","integrity":"/paper/2505.08288/integrity","json":"/paper/2505.08288/citation-record.json","paper":"/paper/2505.08288"},"outbound":[],"paper":{"arxiv_id":"2505.08288","last_updated":"2025-05-13T07:05:27Z","latest_version":1,"primary_category":"stat.ME","snapshot_observed_at":"2026-08-07T15:47:38.832175Z","submitted_at":"2025-05-13T07:05:27Z","title":"High-dimensional Bayesian Tobit regression for censored response with Horseshoe prior"},"reference_resolution":{"displayed":0,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":0,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":0},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"thesis":"As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2505.08288."}