{"as_of":"2026-08-21T21:42:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:efdebcb6c19ca6eeb7d237d889bebc82b56ce3e60b48a0204f08f9dd278c632d","coverage":[{"denominator":9,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":9,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-03T00:14:44.038464Z","state":"measured"},{"denominator":9,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":9,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-21T06:32:19.484+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[],"links":{"evidence":"/evidence","html":"/paper/2602.11467/citation-record","integrity":"/paper/2602.11467/integrity","json":"/paper/2602.11467/citation-record.json","paper":"/paper/2602.11467"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T00:14:43.776261Z","title":"(67) A.2.3","venue":null,"work_id":null,"year":1984},"citing_paper":{"arxiv_id":"2602.11467","last_updated":"2026-06-16T18:55:41Z","snapshot_observed_at":"2026-08-06T18:39:15.009165Z","submitted_at":"2026-02-12T00:55:31Z","title":"PRISM: A 3D Probabilistic Neural Representation for Interpretable Shape Modeling","version":2},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-03T00:14:43.776261Z"},"links":{"citing_paper":"/paper/2602.11467"},"observation_digest":"sha256:8cbd40c4443194824c948b299883048d79ef49d3a928ada4e3b5cb8f9a85956d","observation_id":"29f49951-a1b1-4eef-9223-5985b2bc8f06","resolution":{"observed_at":"2026-08-03T00:14:43.776261Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T00:14:43.021458Z","title":"doi: 10.1007/s10994-021-05946-3","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2602.11467","last_updated":"2026-06-16T18:55:41Z","snapshot_observed_at":"2026-08-06T18:39:15.009165Z","submitted_at":"2026-02-12T00:55:31Z","title":"PRISM: A 3D Probabilistic Neural Representation for Interpretable Shape Modeling","version":2},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-03T00:14:43.021458Z"},"links":{"citing_paper":"/paper/2602.11467"},"observation_digest":"sha256:e00b88574d0e5b97df589c96fe8834da6166c3380d4fc540595d5d09d6d5d2b9","observation_id":"bf95dbea-c592-422e-a167-e81fa8fe7ef9","resolution":{"observed_at":"2026-08-03T00:14:43.021458Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T00:14:43.625256Z","title":"The closed-form Fisher Information for multivariate normal distributions is a classical result (Skovgaard, 1984; Nielsen, 2023)","venue":null,"work_id":null,"year":1999},"citing_paper":{"arxiv_id":"2602.11467","last_updated":"2026-06-16T18:55:41Z","snapshot_observed_at":"2026-08-06T18:39:15.009165Z","submitted_at":"2026-02-12T00:55:31Z","title":"PRISM: A 3D Probabilistic Neural Representation for Interpretable Shape Modeling","version":2},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-03T00:14:43.625256Z"},"links":{"citing_paper":"/paper/2602.11467"},"observation_digest":"sha256:d3d398dfb598cf2fff3383886f49fec02836701c56588eea5640d0e27ea5a933","observation_id":"f8d95e23-0366-4989-ab11-76c0750eea5e","resolution":{"observed_at":"2026-08-03T00:14:43.625256Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T00:14:43.937541Z","title":"The segmentation model was trained on 68 manually annotated CT-segmentation pairs","venue":null,"work_id":null,"year":2013},"citing_paper":{"arxiv_id":"2602.11467","last_updated":"2026-06-16T18:55:41Z","snapshot_observed_at":"2026-08-06T18:39:15.009165Z","submitted_at":"2026-02-12T00:55:31Z","title":"PRISM: A 3D Probabilistic Neural Representation for Interpretable Shape Modeling","version":2},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-03T00:14:43.937541Z"},"links":{"citing_paper":"/paper/2602.11467"},"observation_digest":"sha256:330a31c968753c4d1835f463691bfd1d0d81c0cc76f2057fa7726b264f847fba","observation_id":"0a199e47-d29b-4275-86d7-d05e9d7fe81a","resolution":{"observed_at":"2026-08-03T00:14:43.937541Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T00:14:44.038464Z","title":"As shown in Fig","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2602.11467","last_updated":"2026-06-16T18:55:41Z","snapshot_observed_at":"2026-08-06T18:39:15.009165Z","submitted_at":"2026-02-12T00:55:31Z","title":"PRISM: A 3D Probabilistic Neural Representation for Interpretable Shape Modeling","version":2},"reference_index":1975,"source":"pdf_text","source_observed_at":"2026-08-03T00:14:44.038464Z"},"links":{"citing_paper":"/paper/2602.11467"},"observation_digest":"sha256:fef788df6370d14278dc97bc159eb96f1c2416e02e200c47c9af360e502a13ac","observation_id":"cdcef8f5-a76e-4ee4-bfda-b58836e95718","resolution":{"observed_at":"2026-08-03T00:14:44.038464Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1606.06650","last_updated":"2016-06-21T16:42:20Z","snapshot_observed_at":"2026-08-17T14:21:43.689768Z","submitted_at":"2016-06-21T16:42:20Z","title":"3D U-Net: Learning Dense Volumetric Segmentation from Sparse Annotation","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1606.06650","snapshot_observed_at":"2026-08-03T00:14:43.466714Z","title":null,"venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2602.11467","last_updated":"2026-06-16T18:55:41Z","snapshot_observed_at":"2026-08-06T18:39:15.009165Z","submitted_at":"2026-02-12T00:55:31Z","title":"PRISM: A 3D Probabilistic Neural Representation for Interpretable Shape Modeling","version":2},"reference_index":2016,"source":"pdf_text","source_observed_at":"2026-08-03T00:14:43.466714Z"},"links":{"cited_paper":"/paper/1606.06650","citing_paper":"/paper/2602.11467"},"observation_digest":"sha256:91eb1a630caf7c955ac385f42a96e475a0105ac48b59b3db3167254daaa9c976","observation_id":"2ecf0853-cf73-4c2b-a975-a2fd1e25be79","resolution":{"observed_at":"2026-08-03T00:14:43.466714Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T00:14:42.746201Z","title":"doi: 10.1016/j.inffus.2021.05.008","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2602.11467","last_updated":"2026-06-16T18:55:41Z","snapshot_observed_at":"2026-08-06T18:39:15.009165Z","submitted_at":"2026-02-12T00:55:31Z","title":"PRISM: A 3D Probabilistic Neural Representation for Interpretable Shape Modeling","version":2},"reference_index":2021,"source":"pdf_text","source_observed_at":"2026-08-03T00:14:42.746201Z"},"links":{"citing_paper":"/paper/2602.11467"},"observation_digest":"sha256:62f3a20a7c8fb488d7254b65d13e1664ebf035e29f08f919fd530ebd50cd0f10","observation_id":"2edc2fb2-dea3-4296-a219-a2358ed41184","resolution":{"observed_at":"2026-08-03T00:14:42.746201Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2303.09234","last_updated":"2024-03-14T18:37:07Z","snapshot_observed_at":"2026-08-19T18:50:26.258272Z","submitted_at":"2023-03-16T11:18:04Z","title":"NAISR: A 3D Neural Additive Model for Interpretable Shape Representation","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2303.09234","snapshot_observed_at":"2026-08-03T00:14:43.392451Z","title":"Jungo, A","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2602.11467","last_updated":"2026-06-16T18:55:41Z","snapshot_observed_at":"2026-08-06T18:39:15.009165Z","submitted_at":"2026-02-12T00:55:31Z","title":"PRISM: A 3D Probabilistic Neural Representation for Interpretable Shape Modeling","version":2},"reference_index":2024,"source":"pdf_text","source_observed_at":"2026-08-03T00:14:43.392451Z"},"links":{"cited_paper":"/paper/2303.09234","citing_paper":"/paper/2602.11467"},"observation_digest":"sha256:029d20db432b649c9e83111eed5a6666df2ff0f18bb0b4ecc3450fc9b022a019","observation_id":"de368796-93c0-440b-8b96-1e65788fafff","resolution":{"observed_at":"2026-08-03T00:14:43.392451Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2511.03589","last_updated":"2026-07-29T11:55:47Z","snapshot_observed_at":"2026-08-17T14:01:47.915071Z","submitted_at":"2025-11-05T16:10:02Z","title":"Human Mesh Modeling for Anny Body","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2511.03589","snapshot_observed_at":"2026-08-03T00:14:42.855598Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2602.11467","last_updated":"2026-06-16T18:55:41Z","snapshot_observed_at":"2026-08-06T18:39:15.009165Z","submitted_at":"2026-02-12T00:55:31Z","title":"PRISM: A 3D Probabilistic Neural Representation for Interpretable Shape Modeling","version":2},"reference_index":2025,"source":"pdf_text","source_observed_at":"2026-08-03T00:14:42.855598Z"},"links":{"cited_paper":"/paper/2511.03589","citing_paper":"/paper/2602.11467"},"observation_digest":"sha256:cf5102303eb140d038416d7734c81489abadbf22d9c71bf3fb50b37ae4011582","observation_id":"913db382-1013-479e-a178-9e5cbafa2aab","resolution":{"observed_at":"2026-08-03T00:14:42.855598Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2602.11467","last_updated":"2026-06-16T18:55:41Z","latest_version":2,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-06T18:39:15.009165Z","submitted_at":"2026-02-12T00:55:31Z","title":"PRISM: A 3D Probabilistic Neural Representation for Interpretable Shape Modeling"},"reference_resolution":{"displayed":9,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":9,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":9},"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":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"thesis":"As of 21 August 2026, this Paper Citation Record lists 9 of 9 outbound references and 0 inbound Pith citation observations for arXiv:2602.11467."}