{"as_of":"2026-08-14T09:12:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:56e88d4394833e1d14f314b66f38617cb5c1b8b9639d830299f66766954f6282","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":13,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":13,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-14T06:32:32.682623+00:00","state":"measured"},{"denominator":13,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":13,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-12T17:23:17.883314Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"arxiv_reference","source_observed_at":"2026-07-03T00:47:30.203333Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2303.10528","last_updated":"2023-05-30T16:17:49Z","snapshot_observed_at":"2026-08-13T12:22:04.419103Z","submitted_at":"2023-03-19T01:41:45Z","title":"LNO: Laplace Neural Operator for Solving Differential Equations","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2303.10528","snapshot_observed_at":"2026-08-12T17:23:17.883314Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2411.12726","last_updated":"2024-11-19T18:48:00Z","snapshot_observed_at":"2026-08-13T14:32:30.565697Z","submitted_at":"2024-11-19T18:48:00Z","title":"LazyDINO: Fast, scalable, and efficiently amortized Bayesian inversion via structure-exploiting and surrogate-driven measure transport","version":1},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-08-12T17:23:17.883314Z"},"links":{"cited_paper":"/paper/2303.10528","citing_paper":"/paper/2411.12726"},"observation_digest":"sha256:c0d624d454fdb3a226b284724071d51070d6047c070eab98db8285e8fa1a8cb5","observation_id":"0f7b5d00-d32f-4447-9727-debf8d6f24e5","resolution":{"observed_at":"2026-08-12T17:23:17.883314Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2303.10528","last_updated":"2023-05-30T16:17:49Z","snapshot_observed_at":"2026-08-13T12:22:04.419103Z","submitted_at":"2023-03-19T01:41:45Z","title":"LNO: Laplace Neural Operator for Solving Differential Equations","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2303.10528","snapshot_observed_at":"2026-08-10T22:31:41.747345Z","title":"Lno: Laplace neural operator for solving differential equations","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2501.08339","last_updated":"2025-01-02T19:24:19Z","snapshot_observed_at":"2026-08-13T09:54:49.932751Z","submitted_at":"2025-01-02T19:24:19Z","title":"Operator Learning for Reconstructing Flow Fields from Sparse Measurements: an Energy Transformer Approach","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-10T22:31:41.747345Z"},"links":{"cited_paper":"/paper/2303.10528","citing_paper":"/paper/2501.08339"},"observation_digest":"sha256:499a0a3bdb7279c252f9e7c540f0da84315258023624f3b80665966761d0331e","observation_id":"c5a20c40-718d-49a3-b493-31d1b90d5c12","resolution":{"observed_at":"2026-08-10T22:31:41.747345Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2303.10528","last_updated":"2023-05-30T16:17:49Z","snapshot_observed_at":"2026-08-13T12:22:04.419103Z","submitted_at":"2023-03-19T01:41:45Z","title":"LNO: Laplace Neural Operator for Solving Differential Equations","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2303.10528","snapshot_observed_at":"2026-08-10T17:46:46.872502Z","title":"LNO: Laplace neural oper- ator for solving differential equations,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2501.11937","last_updated":"2025-01-22T03:13:23Z","snapshot_observed_at":"2026-08-13T06:24:51.831819Z","submitted_at":"2025-01-21T07:27:05Z","title":"MeshONet: A Generalizable and Efficient Operator Learning Method for Structured Mesh Generation","version":2},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-10T17:46:46.872502Z"},"links":{"cited_paper":"/paper/2303.10528","citing_paper":"/paper/2501.11937"},"observation_digest":"sha256:a841b95785d21a536aa4a67288697f5f8c0e771895c378883b44306430de53a3","observation_id":"6504ca1c-f9d8-49d1-9a8a-3b2bdf35024e","resolution":{"observed_at":"2026-08-10T17:46:46.872502Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2303.10528","last_updated":"2023-05-30T16:17:49Z","snapshot_observed_at":"2026-08-13T12:22:04.419103Z","submitted_at":"2023-03-19T01:41:45Z","title":"LNO: Laplace Neural Operator for Solving Differential Equations","version":2},"cited_work":{"arxiv_id":"2303.10528","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2303.10528","snapshot_observed_at":"2026-07-03T00:47:30.203333Z","title":"LNO: Laplace Neural Operator for Solving Differential Equations, May 2023","venue":null,"work_id":"81b1100b-087a-4973-b84e-034780076680","year":2023},"citing_paper":{"arxiv_id":"2505.13510","last_updated":"2026-04-22T00:35:04Z","snapshot_observed_at":"2026-08-11T18:23:55.936820Z","submitted_at":"2025-05-16T20:16:14Z","title":"On the definition and importance of interpretability in scientific machine learning","version":3},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-05-22T14:08:37.253192Z"},"links":{"cited_paper":"/paper/2303.10528","citing_paper":"/paper/2505.13510"},"observation_digest":"sha256:42c172759514ab307ac9ad5a5a0fb5c5deffc61b92ea179ce782a471e126d5c4","observation_id":"475205ef-0302-47f6-bcb4-77347db6e7b9","resolution":{"observed_at":"2026-05-22T14:11:38.690127Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2303.10528","last_updated":"2023-05-30T16:17:49Z","snapshot_observed_at":"2026-08-13T12:22:04.419103Z","submitted_at":"2023-03-19T01:41:45Z","title":"LNO: Laplace Neural Operator for Solving Differential Equations","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2303.10528","snapshot_observed_at":"2026-08-07T04:19:37.970292Z","title":"LNO : Laplace neural operator for solving differential equations","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.10973","last_updated":"2025-06-12T17:59:31Z","snapshot_observed_at":"2026-08-11T05:32:22.625605Z","submitted_at":"2025-06-12T17:59:31Z","title":"Principled Approaches for Extending Neural Architectures to Function Spaces for Operator Learning","version":1},"reference_index":13,"source":"arxiv_source","source_observed_at":"2026-08-07T04:19:37.970292Z"},"links":{"cited_paper":"/paper/2303.10528","citing_paper":"/paper/2506.10973"},"observation_digest":"sha256:c06a5274c4b6525ea1ba8a721de7d26f04c2ecfeb99ab5832e39cf5b1ec7b87b","observation_id":"bf8143b8-e235-41b6-aed1-905434b94a15","resolution":{"observed_at":"2026-08-07T04:19:37.970292Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2303.10528","last_updated":"2023-05-30T16:17:49Z","snapshot_observed_at":"2026-08-13T12:22:04.419103Z","submitted_at":"2023-03-19T01:41:45Z","title":"LNO: Laplace Neural Operator for Solving Differential Equations","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2303.10528","snapshot_observed_at":"2026-08-06T19:04:46.316086Z","title":"LNO: Laplace neural operator for solving differential equations","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2507.17763","last_updated":"2025-07-09T11:22:02Z","snapshot_observed_at":"2026-08-13T00:51:45.352305Z","submitted_at":"2025-07-09T11:22:02Z","title":"Multi-Head Neural Operator for Modelling Interfacial Dynamics","version":1},"reference_index":65,"source":"pdf_text","source_observed_at":"2026-08-06T19:04:46.316086Z"},"links":{"cited_paper":"/paper/2303.10528","citing_paper":"/paper/2507.17763"},"observation_digest":"sha256:967220a1324a736ceb33059e9ef375232caf05e7dd3470a3fa21d8cab5900e8d","observation_id":"8b27f88b-2963-468d-911d-cec88c14388f","resolution":{"observed_at":"2026-08-06T19:04:46.316086Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2303.10528","last_updated":"2023-05-30T16:17:49Z","snapshot_observed_at":"2026-08-13T12:22:04.419103Z","submitted_at":"2023-03-19T01:41:45Z","title":"LNO: Laplace Neural Operator for Solving Differential Equations","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2303.10528","snapshot_observed_at":"2026-08-03T08:36:45.428404Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2601.17090","last_updated":"2026-07-13T12:46:39Z","snapshot_observed_at":"2026-08-13T19:13:49.295920Z","submitted_at":"2026-01-23T10:45:52Z","title":"SFO: Learning PDE Operators via Spectral Filtering","version":2},"reference_index":2022,"source":"pdf_text","source_observed_at":"2026-08-03T08:36:45.428404Z"},"links":{"cited_paper":"/paper/2303.10528","citing_paper":"/paper/2601.17090"},"observation_digest":"sha256:f8d991c23a6ef8228ee56a50e84f9df9c73024d68e593111bf2ca81fb05cc64c","observation_id":"f1c3ac8d-025a-4211-ad60-fa8049b0c760","resolution":{"observed_at":"2026-08-03T08:36:45.428404Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2303.10528","last_updated":"2023-05-30T16:17:49Z","snapshot_observed_at":"2026-08-13T12:22:04.419103Z","submitted_at":"2023-03-19T01:41:45Z","title":"LNO: Laplace Neural Operator for Solving Differential Equations","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2303.10528","snapshot_observed_at":"2026-08-02T23:34:43.051423Z","title":"LNO: Laplace Neural Operator for Solving Differential Equations, May 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2602.13513","last_updated":"2026-02-17T20:17:04Z","snapshot_observed_at":"2026-08-09T16:02:11.525422Z","submitted_at":"2026-02-13T22:44:33Z","title":"Learning Gradient Flow: Using Equation Discovery to Accelerate Engineering Optimization","version":2},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-02T23:34:43.051423Z"},"links":{"cited_paper":"/paper/2303.10528","citing_paper":"/paper/2602.13513"},"observation_digest":"sha256:561b6c2bb6065a9826a4a48684d916c2e8bb27cc2bf4619de03dbb1d2b022b73","observation_id":"744825c7-0c6f-4051-b81a-1fef07295aa8","resolution":{"observed_at":"2026-08-02T23:34:43.051423Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2303.10528","last_updated":"2023-05-30T16:17:49Z","snapshot_observed_at":"2026-08-13T12:22:04.419103Z","submitted_at":"2023-03-19T01:41:45Z","title":"LNO: Laplace Neural Operator for Solving Differential Equations","version":2},"cited_work":{"arxiv_id":"2303.10528","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2303.10528","snapshot_observed_at":"2026-07-03T00:47:30.203333Z","title":"LNO: Laplace Neural Operator for Solving Differential Equations, May 2023","venue":null,"work_id":"81b1100b-087a-4973-b84e-034780076680","year":2023},"citing_paper":{"arxiv_id":"2605.21348","last_updated":"2026-05-20T16:13:53Z","snapshot_observed_at":"2026-08-12T09:53:55.012877Z","submitted_at":"2026-05-20T16:13:53Z","title":"Data-Efficient Neural Operator Training via Physics-Based Active Learning","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-05-21T05:33:00.817862Z"},"links":{"cited_paper":"/paper/2303.10528","citing_paper":"/paper/2605.21348"},"observation_digest":"sha256:2129e43b79215fd919025147569cd97326edf69f773b7b35e004564642b71154","observation_id":"4057c717-9828-4945-9bb9-ba602e13c36f","resolution":{"observed_at":"2026-05-21T05:33:58.514919Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2303.10528","last_updated":"2023-05-30T16:17:49Z","snapshot_observed_at":"2026-08-13T12:22:04.419103Z","submitted_at":"2023-03-19T01:41:45Z","title":"LNO: Laplace Neural Operator for Solving Differential Equations","version":2},"cited_work":{"arxiv_id":"2303.10528","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2303.10528","snapshot_observed_at":"2026-07-03T00:47:30.203333Z","title":"LNO: Laplace Neural Operator for Solving Differential Equations, May 2023","venue":null,"work_id":"81b1100b-087a-4973-b84e-034780076680","year":2023},"citing_paper":{"arxiv_id":"2605.22338","last_updated":"2026-05-21T11:24:48Z","snapshot_observed_at":"2026-08-06T08:55:16.227907Z","submitted_at":"2026-05-21T11:24:48Z","title":"Physics-Informed Generative Solver: Bridging Data-Driven Priors and Conservation Laws for Stable Spatiotemporal Field Reconstruction","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-05-22T07:18:38.258250Z"},"links":{"cited_paper":"/paper/2303.10528","citing_paper":"/paper/2605.22338"},"observation_digest":"sha256:92a15f6c689e678a1e63f017d0969d2410da3f0032c6bbc430c566ce8305ccbd","observation_id":"d03bcad5-8cfc-4de8-89d6-cf39cb13c339","resolution":{"observed_at":"2026-05-22T07:21:12.987674Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2303.10528","last_updated":"2023-05-30T16:17:49Z","snapshot_observed_at":"2026-08-13T12:22:04.419103Z","submitted_at":"2023-03-19T01:41:45Z","title":"LNO: Laplace Neural Operator for Solving Differential Equations","version":2},"cited_work":{"arxiv_id":"2303.10528","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2303.10528","snapshot_observed_at":"2026-07-03T00:47:30.203333Z","title":"LNO: Laplace Neural Operator for Solving Differential Equations, May 2023","venue":null,"work_id":"81b1100b-087a-4973-b84e-034780076680","year":2023},"citing_paper":{"arxiv_id":"2605.24658","last_updated":"2026-05-23T16:58:37Z","snapshot_observed_at":"2026-08-12T12:34:45.555123Z","submitted_at":"2026-05-23T16:58:37Z","title":"WLNO: Wavelet-Laplace Neural Operator for Solving Partial Differential Equations","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-06-30T14:57:17.751127Z"},"links":{"cited_paper":"/paper/2303.10528","citing_paper":"/paper/2605.24658"},"observation_digest":"sha256:7d0479af3e2e58b61f3405954033594af37e9c09bb3c28eed9be5cbb9cc11fd7","observation_id":"52ba2330-5b5d-41d9-93d9-5d549cacfd99","resolution":{"observed_at":"2026-06-30T15:04:46.397611Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2303.10528","last_updated":"2023-05-30T16:17:49Z","snapshot_observed_at":"2026-08-13T12:22:04.419103Z","submitted_at":"2023-03-19T01:41:45Z","title":"LNO: Laplace Neural Operator for Solving Differential Equations","version":2},"cited_work":{"arxiv_id":"2303.10528","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2303.10528","snapshot_observed_at":"2026-07-03T00:47:30.203333Z","title":"LNO: Laplace Neural Operator for Solving Differential Equations, May 2023","venue":null,"work_id":"81b1100b-087a-4973-b84e-034780076680","year":2023},"citing_paper":{"arxiv_id":"2606.08956","last_updated":"2026-07-27T01:57:24Z","snapshot_observed_at":"2026-08-03T21:37:59.460585Z","submitted_at":"2026-06-08T02:58:15Z","title":"From inverse problems to neural operators: prediction, mechanism, and generalization of data-driven models","version":2},"reference_index":65,"source":"pdf_text","source_observed_at":"2026-06-27T17:03:15.379147Z"},"links":{"cited_paper":"/paper/2303.10528","citing_paper":"/paper/2606.08956"},"observation_digest":"sha256:837ce18a645a969ac9366964e2ed2839e17df7d901eb3b64841792a22752ab7a","observation_id":"ab64489b-fb9e-4f0d-b306-5a1e3927de6c","resolution":{"observed_at":"2026-07-03T00:47:30.205517Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2303.10528","last_updated":"2023-05-30T16:17:49Z","snapshot_observed_at":"2026-08-13T12:22:04.419103Z","submitted_at":"2023-03-19T01:41:45Z","title":"LNO: Laplace Neural Operator for Solving Differential Equations","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2303.10528","snapshot_observed_at":"2026-08-02T12:05:40.237401Z","title":"LNO: Laplace Neural Operator for Solving Differential Equations, May 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2606.08956","last_updated":"2026-07-27T01:57:24Z","snapshot_observed_at":"2026-08-03T21:37:59.460585Z","submitted_at":"2026-06-08T02:58:15Z","title":"From inverse problems to neural operators: prediction, mechanism, and generalization of data-driven models","version":3},"reference_index":65,"source":"pdf_text","source_observed_at":"2026-08-02T12:05:40.237401Z"},"links":{"cited_paper":"/paper/2303.10528","citing_paper":"/paper/2606.08956"},"observation_digest":"sha256:6b221cab0b1d015973190c2c987abcd787d7ee0b3d81aceb77958f59bb574a13","observation_id":"4f8f0b6a-ff01-45c8-8d33-f3995c4abb92","resolution":{"observed_at":"2026-08-02T12:05:40.237401Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2303.10528/citation-record","integrity":"/paper/2303.10528/integrity","json":"/paper/2303.10528/citation-record.json","paper":"/paper/2303.10528"},"outbound":[],"paper":{"arxiv_id":"2303.10528","last_updated":"2023-05-30T16:17:49Z","latest_version":2,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-13T12:22:04.419103Z","submitted_at":"2023-03-19T01:41:45Z","title":"LNO: Laplace Neural Operator for Solving Differential Equations"},"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":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"thesis":"As of 14 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 13 inbound Pith citation observations for arXiv:2303.10528."}