{"as_of":"2026-08-14T11:24:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:723ed7b6a4a9157b726c7a96556bc750293bfc7ae59b1d426d8ce64e89bcf3d4","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":5,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":5,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-14T06:32:32.682623+00:00","state":"measured"},{"denominator":5,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":5,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-12T15:17:15.746020Z","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":"2026-07-03T19:58:54.774638Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2106.11271","last_updated":"2022-04-01T13:07:13Z","snapshot_observed_at":"2026-08-09T13:30:50.160728Z","submitted_at":"2021-06-21T17:18:24Z","title":"Jet tomography in heavy ion collisions with deep learning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2106.11271","snapshot_observed_at":"2026-08-12T15:17:15.746020Z","title":null,"venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2411.14552","last_updated":"2024-12-10T14:00:09Z","snapshot_observed_at":"2026-08-13T04:13:50.545247Z","submitted_at":"2024-11-21T19:46:55Z","title":"Constraining Jet Quenching in Heavy-Ion Collisions with Bayesian Inference","version":2},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-12T15:17:15.746020Z"},"links":{"cited_paper":"/paper/2106.11271","citing_paper":"/paper/2411.14552"},"observation_digest":"sha256:cb19424a658c3821c6a0f43d8fbaa9fd463643ac502f46698f36a1f1ffb15d6b","observation_id":"33ff444b-0d70-4c16-8fc6-44a38b5ba8bd","resolution":{"observed_at":"2026-08-12T15:17:15.746020Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2106.11271","last_updated":"2022-04-01T13:07:13Z","snapshot_observed_at":"2026-08-09T13:30:50.160728Z","submitted_at":"2021-06-21T17:18:24Z","title":"Jet tomography in heavy ion collisions with deep learning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2106.11271","snapshot_observed_at":"2026-08-06T19:14:52.872798Z","title":null,"venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2507.06291","last_updated":"2026-07-03T08:32:24Z","snapshot_observed_at":"2026-08-09T19:23:33.388729Z","submitted_at":"2025-07-08T18:00:01Z","title":"High-Dimensional Unfolding in Large Backgrounds","version":2},"reference_index":57,"source":"pdf_text","source_observed_at":"2026-08-06T19:14:52.872798Z"},"links":{"cited_paper":"/paper/2106.11271","citing_paper":"/paper/2507.06291"},"observation_digest":"sha256:10081f202ccb5d2b449922eae4f4be03e557c7dde6e17e6e29687bad80660301","observation_id":"c5ccc36d-826b-43bd-bda1-a36e9fcac6e5","resolution":{"observed_at":"2026-08-06T19:14:52.872798Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2106.11271","last_updated":"2022-04-01T13:07:13Z","snapshot_observed_at":"2026-08-09T13:30:50.160728Z","submitted_at":"2021-06-21T17:18:24Z","title":"Jet tomography in heavy ion collisions with deep learning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2106.11271","snapshot_observed_at":"2026-08-03T08:12:16.724975Z","title":null,"venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2601.18133","last_updated":"2026-06-18T06:34:56Z","snapshot_observed_at":"2026-08-08T20:05:27.581251Z","submitted_at":"2026-01-26T04:31:07Z","title":"Heavy Quarkonium Spectrum and Decay Constants from a Neural-Network-Based Holographic Model","version":4},"reference_index":67,"source":"pdf_text","source_observed_at":"2026-08-03T08:12:16.724975Z"},"links":{"cited_paper":"/paper/2106.11271","citing_paper":"/paper/2601.18133"},"observation_digest":"sha256:998dafbd926325e76e93741048b541ae79f7c2017a67773da2bba75df6dc845a","observation_id":"7a2a26ed-f75c-4848-bcc0-c1800ee04c8c","resolution":{"observed_at":"2026-08-03T08:12:16.724975Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2106.11271","last_updated":"2022-04-01T13:07:13Z","snapshot_observed_at":"2026-08-09T13:30:50.160728Z","submitted_at":"2021-06-21T17:18:24Z","title":"Jet tomography in heavy ion collisions with deep learning","version":2},"cited_work":{"arxiv_id":"2106.11271","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2106.11271","snapshot_observed_at":"2026-07-03T19:58:54.774638Z","title":"2106.11271 , archiveprefix =","venue":null,"work_id":"9a6ff0da-3c54-4012-879d-59bf61171052","year":2022},"citing_paper":{"arxiv_id":"2604.09198","last_updated":"2026-04-14T14:34:07Z","snapshot_observed_at":"2026-08-02T19:01:29.778155Z","submitted_at":"2026-04-10T10:33:40Z","title":"Unified Extraction of In-Medium Heavy Quark Potentials from RHIC to LHC Energies via Deep Learning","version":2},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-05-10T17:23:12.933048Z"},"links":{"cited_paper":"/paper/2106.11271","citing_paper":"/paper/2604.09198"},"observation_digest":"sha256:75f014d124a3cf8be62c83aea72f3e634f10d5e604fa582ba1b73c892bdabbbf","observation_id":"66b2a6dd-4f48-4ed6-bb40-1df7798ccaa0","resolution":{"observed_at":"2026-05-11T06:56:00.360124Z","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":"2106.11271","last_updated":"2022-04-01T13:07:13Z","snapshot_observed_at":"2026-08-09T13:30:50.160728Z","submitted_at":"2021-06-21T17:18:24Z","title":"Jet tomography in heavy ion collisions with deep learning","version":2},"cited_work":{"arxiv_id":"2106.11271","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2106.11271","snapshot_observed_at":"2026-07-03T19:58:54.774638Z","title":"2106.11271 , archiveprefix =","venue":null,"work_id":"9a6ff0da-3c54-4012-879d-59bf61171052","year":2022},"citing_paper":{"arxiv_id":"2607.01354","last_updated":"2026-07-01T18:11:57Z","snapshot_observed_at":"2026-08-12T12:40:33.993995Z","submitted_at":"2026-07-01T18:11:57Z","title":"Local Conformal Predictions for Calibrated Surrogates","version":1},"reference_index":216,"source":"arxiv_source","source_observed_at":"2026-07-03T19:29:34.070294Z"},"links":{"cited_paper":"/paper/2106.11271","citing_paper":"/paper/2607.01354"},"observation_digest":"sha256:81612d9805ff9490e89dfe026eb8fbe2990e1b58d7bbc9beb2cb943024ef09eb","observation_id":"96863c21-b3ef-40ce-859c-7257c5ea908e","resolution":{"observed_at":"2026-07-03T19:58:54.775947Z","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"}}],"links":{"evidence":"/evidence","html":"/paper/2106.11271/citation-record","integrity":"/paper/2106.11271/integrity","json":"/paper/2106.11271/citation-record.json","paper":"/paper/2106.11271"},"outbound":[],"paper":{"arxiv_id":"2106.11271","last_updated":"2022-04-01T13:07:13Z","latest_version":2,"primary_category":"hep-ph","snapshot_observed_at":"2026-08-09T13:30:50.160728Z","submitted_at":"2021-06-21T17:18:24Z","title":"Jet tomography in heavy ion collisions with deep learning"},"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 5 inbound Pith citation observations for arXiv:2106.11271."}