{"as_of":"2026-08-10T09:25:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:4ae0ec48588d7cf77d7179675dba7a4aa605b42d9f0289ce023016fe69e5340e","coverage":[{"denominator":14,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":14,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-09T04:27:26.706407Z","state":"measured"},{"denominator":14,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":14,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-10T06:31:04.303077+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/2502.05222/citation-record","integrity":"/paper/2502.05222/integrity","json":"/paper/2502.05222/citation-record.json","paper":"/paper/2502.05222"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T04:27:26.652896Z","title":"Aliev, A","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2502.05222","last_updated":"2025-02-05T20:45:00Z","snapshot_observed_at":"2026-08-09T04:20:28.480786Z","submitted_at":"2025-02-05T20:45:00Z","title":"VistaFlow: Photorealistic Volumetric Reconstruction with Dynamic Resolution Management via Q-Learning","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-09T04:27:26.652896Z"},"links":{"citing_paper":"/paper/2502.05222"},"observation_digest":"sha256:bd7067df6733af2f5143113322ca91b23c22636bebaf5a5446aba2c8751ef852","observation_id":"393d9ec8-aa57-43e8-bbe2-e1bdf155bc51","resolution":{"observed_at":"2026-08-09T04:27:26.652896Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2103.13415","last_updated":"2021-08-14T00:15:45Z","snapshot_observed_at":"2026-08-03T19:38:13.423842Z","submitted_at":"2021-03-24T18:02:11Z","title":"Mip-NeRF: A Multiscale Representation for Anti-Aliasing Neural Radiance Fields","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2103.13415","snapshot_observed_at":"2026-08-09T04:27:26.657447Z","title":null,"venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2502.05222","last_updated":"2025-02-05T20:45:00Z","snapshot_observed_at":"2026-08-09T04:20:28.480786Z","submitted_at":"2025-02-05T20:45:00Z","title":"VistaFlow: Photorealistic Volumetric Reconstruction with Dynamic Resolution Management via Q-Learning","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-09T04:27:26.657447Z"},"links":{"cited_paper":"/paper/2103.13415","citing_paper":"/paper/2502.05222"},"observation_digest":"sha256:4dc3a815c62966d829c959da9c4faa51610e9aae7ebcd9b9b7793c9bb701074c","observation_id":"7b0571bd-057b-4e0f-8cdc-476c09748eef","resolution":{"observed_at":"2026-08-09T04:27:26.657447Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2208.00277","last_updated":"2023-05-30T03:49:00Z","snapshot_observed_at":"2026-07-06T13:36:58.879342Z","submitted_at":"2022-07-30T17:14:14Z","title":"MobileNeRF: Exploiting the Polygon Rasterization Pipeline for Efficient Neural Field Rendering on Mobile Architectures","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2208.00277","snapshot_observed_at":"2026-08-09T04:27:26.661806Z","title":null,"venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2502.05222","last_updated":"2025-02-05T20:45:00Z","snapshot_observed_at":"2026-08-09T04:20:28.480786Z","submitted_at":"2025-02-05T20:45:00Z","title":"VistaFlow: Photorealistic Volumetric Reconstruction with Dynamic Resolution Management via Q-Learning","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-09T04:27:26.661806Z"},"links":{"cited_paper":"/paper/2208.00277","citing_paper":"/paper/2502.05222"},"observation_digest":"sha256:424c6c3802fe034c84511de5b0cbd0ea4bf89b642a13ff2e88b73615ef24dab8","observation_id":"1efa47f1-3a87-4cf9-ac1c-3193380d4b76","resolution":{"observed_at":"2026-08-09T04:27:26.661806Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2103.10380","last_updated":"2021-04-15T11:01:16Z","snapshot_observed_at":"2026-07-06T10:51:16.166605Z","submitted_at":"2021-03-18T17:09:12Z","title":"FastNeRF: High-Fidelity Neural Rendering at 200FPS","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2103.10380","snapshot_observed_at":"2026-08-09T04:27:26.666098Z","title":null,"venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2502.05222","last_updated":"2025-02-05T20:45:00Z","snapshot_observed_at":"2026-08-09T04:20:28.480786Z","submitted_at":"2025-02-05T20:45:00Z","title":"VistaFlow: Photorealistic Volumetric Reconstruction with Dynamic Resolution Management via Q-Learning","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-09T04:27:26.666098Z"},"links":{"cited_paper":"/paper/2103.10380","citing_paper":"/paper/2502.05222"},"observation_digest":"sha256:e091c5f97bcfdc7484786f994e4c422733350c7609db65f1c97ddf2fbb739685","observation_id":"91841c58-47e6-4dfd-ad48-f6a26206aad9","resolution":{"observed_at":"2026-08-09T04:27:26.666098Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2308.04079","last_updated":"2023-08-08T06:37:06Z","snapshot_observed_at":"2026-08-09T22:10:08.471178Z","submitted_at":"2023-08-08T06:37:06Z","title":"3D Gaussian Splatting for Real-Time Radiance Field Rendering","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2308.04079","snapshot_observed_at":"2026-08-09T04:27:26.670501Z","title":"Kerbl, G","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2502.05222","last_updated":"2025-02-05T20:45:00Z","snapshot_observed_at":"2026-08-09T04:20:28.480786Z","submitted_at":"2025-02-05T20:45:00Z","title":"VistaFlow: Photorealistic Volumetric Reconstruction with Dynamic Resolution Management via Q-Learning","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-09T04:27:26.670501Z"},"links":{"cited_paper":"/paper/2308.04079","citing_paper":"/paper/2502.05222"},"observation_digest":"sha256:08768f8ff37e46e1097954b3127f0625f8791db856991d0de46faf5d41265743","observation_id":"6d5ba0e2-cc92-4e70-a589-1eeb4313536a","resolution":{"observed_at":"2026-08-09T04:27:26.670501Z","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":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T04:27:27.210060Z","title":"Knapitsch, J","venue":null,"work_id":"b190dc50-cc15-4184-bbca-cf6f49b675fa","year":2017},"citing_paper":{"arxiv_id":"2502.05222","last_updated":"2025-02-05T20:45:00Z","snapshot_observed_at":"2026-08-09T04:20:28.480786Z","submitted_at":"2025-02-05T20:45:00Z","title":"VistaFlow: Photorealistic Volumetric Reconstruction with Dynamic Resolution Management via Q-Learning","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-09T04:27:26.675008Z"},"links":{"citing_paper":"/paper/2502.05222"},"observation_digest":"sha256:45ff565cfa4fba869619a82f6977647c899edc2efed9fe8470af0d18c3921c3d","observation_id":"8e8b60d7-14a9-4fc7-9536-a068b258cbdb","resolution":{"observed_at":"2026-08-09T04:27:27.213938Z","resolver_source":"arxiv_id_nonexistent","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T04:27:27.233766Z","title":"Mildenhall, P","venue":null,"work_id":"a9ae765a-6e35-4f3e-9baa-b7563bb0e94e","year":null},"citing_paper":{"arxiv_id":"2502.05222","last_updated":"2025-02-05T20:45:00Z","snapshot_observed_at":"2026-08-09T04:20:28.480786Z","submitted_at":"2025-02-05T20:45:00Z","title":"VistaFlow: Photorealistic Volumetric Reconstruction with Dynamic Resolution Management via Q-Learning","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-09T04:27:26.679185Z"},"links":{"citing_paper":"/paper/2502.05222"},"observation_digest":"sha256:1e99f5831021ab42dbcddb4be33498f02d862a78de871e7d62f3fcb2e13bad3d","observation_id":"24e78ca9-8530-4fc5-9815-d6d493815e71","resolution":{"observed_at":"2026-08-09T04:27:27.238104Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1901.05103","last_updated":"2019-01-16T01:21:27Z","snapshot_observed_at":"2026-07-06T07:26:59.288200Z","submitted_at":"2019-01-16T01:21:27Z","title":"DeepSDF: Learning Continuous Signed Distance Functions for Shape Representation","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1901.05103","snapshot_observed_at":"2026-08-09T04:27:26.686993Z","title":null,"venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2502.05222","last_updated":"2025-02-05T20:45:00Z","snapshot_observed_at":"2026-08-09T04:20:28.480786Z","submitted_at":"2025-02-05T20:45:00Z","title":"VistaFlow: Photorealistic Volumetric Reconstruction with Dynamic Resolution Management via Q-Learning","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-09T04:27:26.686993Z"},"links":{"cited_paper":"/paper/1901.05103","citing_paper":"/paper/2502.05222"},"observation_digest":"sha256:99b6704360b0df57887692110539242a7d735e9096817e45eb599e7508b91aea","observation_id":"5c513da5-54ab-405f-ae1b-86080d74fa24","resolution":{"observed_at":"2026-08-09T04:27:26.686993Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2111.03643","last_updated":"2021-11-05T17:50:44Z","snapshot_observed_at":"2026-08-08T00:41:13.040044Z","submitted_at":"2021-11-05T17:50:44Z","title":"TermiNeRF: Ray Termination Prediction for Efficient Neural Rendering","version":1},"cited_work":{"arxiv_id":"2111.03643","doi":"10.48550/arxiv.2111.03643","metadata_source":"pith","pith_arxiv_id":"2111.03643","snapshot_observed_at":"2026-08-10T05:30:23.456663Z","title":"TermiNeRF: Ray Termination Prediction for Efficient Neural Rendering","venue":"cs.CV","work_id":"018e6b06-960d-4e45-813b-6d9d82fe9bdf","year":2021},"citing_paper":{"arxiv_id":"2502.05222","last_updated":"2025-02-05T20:45:00Z","snapshot_observed_at":"2026-08-09T04:20:28.480786Z","submitted_at":"2025-02-05T20:45:00Z","title":"VistaFlow: Photorealistic Volumetric Reconstruction with Dynamic Resolution Management via Q-Learning","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-09T04:27:26.690986Z"},"links":{"cited_paper":"/paper/2111.03643","citing_paper":"/paper/2502.05222"},"observation_digest":"sha256:bad7cc6aa5effbe7ae29b3357d72691263248343e1dd9ce7cca637ca2bfdc62b","observation_id":"a5fd3117-b43e-4e51-ad31-e11281d2b6cd","resolution":{"observed_at":"2026-08-09T04:27:26.774593Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2103.13744","last_updated":"2021-08-02T15:58:25Z","snapshot_observed_at":"2026-08-06T01:18:28.697493Z","submitted_at":"2021-03-25T10:53:05Z","title":"KiloNeRF: Speeding up Neural Radiance Fields with Thousands of Tiny MLPs","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2103.13744","snapshot_observed_at":"2026-08-09T04:27:26.694839Z","title":"Reiser, S","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2502.05222","last_updated":"2025-02-05T20:45:00Z","snapshot_observed_at":"2026-08-09T04:20:28.480786Z","submitted_at":"2025-02-05T20:45:00Z","title":"VistaFlow: Photorealistic Volumetric Reconstruction with Dynamic Resolution Management via Q-Learning","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-09T04:27:26.694839Z"},"links":{"cited_paper":"/paper/2103.13744","citing_paper":"/paper/2502.05222"},"observation_digest":"sha256:2004294dbfe606b22bd5e9f7fb961797270b3d09b946c65e24fe945a194332f7","observation_id":"8fee105a-0814-4afc-92b6-e48849490cb9","resolution":{"observed_at":"2026-08-09T04:27:26.694839Z","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":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T04:27:26.998772Z","title":null,"venue":null,"work_id":"591b182c-964e-4c28-80f0-8c47ca325057","year":2002},"citing_paper":{"arxiv_id":"2502.05222","last_updated":"2025-02-05T20:45:00Z","snapshot_observed_at":"2026-08-09T04:20:28.480786Z","submitted_at":"2025-02-05T20:45:00Z","title":"VistaFlow: Photorealistic Volumetric Reconstruction with Dynamic Resolution Management via Q-Learning","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-09T04:27:26.698625Z"},"links":{"citing_paper":"/paper/2502.05222"},"observation_digest":"sha256:3a31746fc78cd79ae541d14f57c2d5b15c043fec0e77c2c0509cd27b839c134a","observation_id":"b16d4253-dbd9-4937-b73c-67d2be45fd63","resolution":{"observed_at":"2026-08-09T04:27:27.002430Z","resolver_source":"arxiv_id_nonexistent","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2112.05131","last_updated":"2021-12-09T18:59:12Z","snapshot_observed_at":"2026-08-10T07:56:40.570069Z","submitted_at":"2021-12-09T18:59:12Z","title":"Plenoxels: Radiance Fields without Neural Networks","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2112.05131","snapshot_observed_at":"2026-08-09T04:27:26.702446Z","title":null,"venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2502.05222","last_updated":"2025-02-05T20:45:00Z","snapshot_observed_at":"2026-08-09T04:20:28.480786Z","submitted_at":"2025-02-05T20:45:00Z","title":"VistaFlow: Photorealistic Volumetric Reconstruction with Dynamic Resolution Management via Q-Learning","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-09T04:27:26.702446Z"},"links":{"cited_paper":"/paper/2112.05131","citing_paper":"/paper/2502.05222"},"observation_digest":"sha256:aedd33f954915200c6d520610e09d656af5392782d182a6752fcca4e91e55483","observation_id":"96cba296-492e-44a6-a1eb-81c76865950d","resolution":{"observed_at":"2026-08-09T04:27:26.702446Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2103.14024","last_updated":"2021-08-17T06:19:00Z","snapshot_observed_at":"2026-07-06T10:53:28.085825Z","submitted_at":"2021-03-25T17:59:06Z","title":"PlenOctrees for Real-time Rendering of Neural Radiance Fields","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2103.14024","snapshot_observed_at":"2026-08-09T04:27:26.706407Z","title":null,"venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2502.05222","last_updated":"2025-02-05T20:45:00Z","snapshot_observed_at":"2026-08-09T04:20:28.480786Z","submitted_at":"2025-02-05T20:45:00Z","title":"VistaFlow: Photorealistic Volumetric Reconstruction with Dynamic Resolution Management via Q-Learning","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-09T04:27:26.706407Z"},"links":{"cited_paper":"/paper/2103.14024","citing_paper":"/paper/2502.05222"},"observation_digest":"sha256:b3b239ee6369ac207bd4938fe2ec5dbdfd2fd927d34dad01b1adb8cfa21f9684","observation_id":"60283f5c-f6cc-44de-a156-ddcae010d888","resolution":{"observed_at":"2026-08-09T04:27:26.706407Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2003.08934","last_updated":"2020-08-03T22:17:31Z","snapshot_observed_at":"2026-08-07T21:12:33.939201Z","submitted_at":"2020-03-19T17:57:23Z","title":"NeRF: Representing Scenes as Neural Radiance Fields for View Synthesis","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2003.08934","snapshot_observed_at":"2026-08-09T04:27:26.683158Z","title":"arXiv (Cornell University) (2020)","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2502.05222","last_updated":"2025-02-05T20:45:00Z","snapshot_observed_at":"2026-08-09T04:20:28.480786Z","submitted_at":"2025-02-05T20:45:00Z","title":"VistaFlow: Photorealistic Volumetric Reconstruction with Dynamic Resolution Management via Q-Learning","version":1},"reference_index":2020,"source":"pdf_text","source_observed_at":"2026-08-09T04:27:26.683158Z"},"links":{"cited_paper":"/paper/2003.08934","citing_paper":"/paper/2502.05222"},"observation_digest":"sha256:38652fbde6c5ab61e1d8e20eff0ac6bde68b925b1d20e5a0141c3dc144ce81d5","observation_id":"55fa42c8-1456-4153-956c-1e91eae1af5a","resolution":{"observed_at":"2026-08-09T04:27:26.683158Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2502.05222","last_updated":"2025-02-05T20:45:00Z","latest_version":1,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-09T04:20:28.480786Z","submitted_at":"2025-02-05T20:45:00Z","title":"VistaFlow: Photorealistic Volumetric Reconstruction with Dynamic Resolution Management via Q-Learning"},"reference_resolution":{"displayed":14,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":10,"verified_exact":3,"verified_fuzzy":1},"total_outbound_references":14},"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":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"thesis":"As of 10 August 2026, this Paper Citation Record lists 14 of 14 outbound references and 0 inbound Pith citation observations for arXiv:2502.05222."}