{"as_of":"2026-08-10T05:59:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:c43506d948c28f6804229a1301ed6bfb1c33ac2714cb32ff9f6f4ceba49d1c26","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":7,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":7,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-09T06:31:02.800959+00:00","state":"measured"},{"denominator":7,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":7,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-08T18:56:27.534247Z","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":"2026-05-24T15:09:36.818046Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"1609.07196","last_updated":"2024-05-11T23:37:54Z","snapshot_observed_at":"2026-08-09T19:30:59.179900Z","submitted_at":"2016-09-23T00:35:53Z","title":"Review of multi-fidelity models","version":6},"cited_work":{"arxiv_id":"1609.07196","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"1609.07196","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Review of multi-ﬁdelity models","venue":null,"work_id":"690badb0-8565-42b6-98a9-364a6711161f","year":2016},"citing_paper":{"arxiv_id":"1907.11739","last_updated":"2019-07-26T18:17:45Z","snapshot_observed_at":"2026-07-06T08:10:34.301657Z","submitted_at":"2019-07-26T18:17:45Z","title":"A Strategy for Adaptive Sampling of Multi-fidelity Gaussian Process to Reduce Predictive Uncertainty","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-05-24T15:08:15.295658Z"},"links":{"cited_paper":"/paper/1609.07196","citing_paper":"/paper/1907.11739"},"observation_digest":"sha256:b165108ac1d5e98ac92ba28a52cce662708b2a6ec31f5f1050de590c23f9ed6f","observation_id":"526288da-707f-4b4b-8d88-ec7267f7457e","resolution":{"observed_at":"2026-05-24T15:09:36.820833Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1609.07196","last_updated":"2024-05-11T23:37:54Z","snapshot_observed_at":"2026-08-09T19:30:59.179900Z","submitted_at":"2016-09-23T00:35:53Z","title":"Review of multi-fidelity models","version":6},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1609.07196","snapshot_observed_at":"2026-08-08T18:56:27.534247Z","title":"Review of multi-fidelity models","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2502.05565","last_updated":"2025-02-08T13:27:10Z","snapshot_observed_at":"2026-08-08T18:47:01.917929Z","submitted_at":"2025-02-08T13:27:10Z","title":"Multi-Scale Conformal Prediction: A Theoretical Framework with Coverage Guarantees","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-08T18:56:27.534247Z"},"links":{"cited_paper":"/paper/1609.07196","citing_paper":"/paper/2502.05565"},"observation_digest":"sha256:1a33c0287c92cc1e0784a19181cde7fb0fbdea84ac01adcda111e9125f714596","observation_id":"a178935d-e2dd-4f81-8efe-596d9006187c","resolution":{"observed_at":"2026-08-08T18:56:27.534247Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1609.07196","last_updated":"2024-05-11T23:37:54Z","snapshot_observed_at":"2026-08-09T19:30:59.179900Z","submitted_at":"2016-09-23T00:35:53Z","title":"Review of multi-fidelity models","version":6},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1609.07196","snapshot_observed_at":"2026-08-06T14:25:55.283842Z","title":null,"venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2507.22079","last_updated":"2025-07-25T15:55:59Z","snapshot_observed_at":"2026-08-08T19:34:23.752724Z","submitted_at":"2025-07-25T15:55:59Z","title":"Multi-fidelity Bayesian Data-Driven Design of Energy Absorbing Spinodoid Cellular Structures","version":1},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-08-06T14:25:55.283842Z"},"links":{"cited_paper":"/paper/1609.07196","citing_paper":"/paper/2507.22079"},"observation_digest":"sha256:c94366ea7bb29d4f5df178ed110be723e0942c99468bf490c5dd725f4ef7656f","observation_id":"d307959c-6c6c-4fec-931e-c848131ec3fd","resolution":{"observed_at":"2026-08-06T14:25:55.283842Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1609.07196","last_updated":"2024-05-11T23:37:54Z","snapshot_observed_at":"2026-08-09T19:30:59.179900Z","submitted_at":"2016-09-23T00:35:53Z","title":"Review of multi-fidelity models","version":6},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1609.07196","snapshot_observed_at":"2026-08-03T20:05:39.883542Z","title":"Review of multi-fidelity models,","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2511.21274","last_updated":"2026-06-29T07:23:24Z","snapshot_observed_at":"2026-08-03T20:05:35.637126Z","submitted_at":"2025-11-26T10:56:12Z","title":"Multiport Analytical Pixel Electromagnetic Simulator (MAPES) for AI-assisted RFIC and Microwave Circuit Design","version":3},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-03T20:05:39.883542Z"},"links":{"cited_paper":"/paper/1609.07196","citing_paper":"/paper/2511.21274"},"observation_digest":"sha256:6370bc9bb8d4c9e39e1123c7f4dd4b6ea8d2963d3d12f3abedbbe3105537ad83","observation_id":"3d1d41d0-c17c-452a-a8b0-8f8d4c37d9ba","resolution":{"observed_at":"2026-08-03T20:05:39.883542Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1609.07196","last_updated":"2024-05-11T23:37:54Z","snapshot_observed_at":"2026-08-09T19:30:59.179900Z","submitted_at":"2016-09-23T00:35:53Z","title":"Review of multi-fidelity models","version":6},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1609.07196","snapshot_observed_at":"2026-07-13T20:27:45.196743Z","title":"Review of multi-fidelity models,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2603.22050","last_updated":"2026-06-24T13:15:28Z","snapshot_observed_at":"2026-08-08T12:54:20.093424Z","submitted_at":"2026-03-23T14:49:38Z","title":"Multifidelity-Augmented Gaussian Process Inputs for Surrogate Modeling from Scarce Data","version":2},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-07-13T20:27:45.196743Z"},"links":{"cited_paper":"/paper/1609.07196","citing_paper":"/paper/2603.22050"},"observation_digest":"sha256:2bcaa2443d6125e695ab583e1548ab7d41fabc9fdb32bd9b828583706bd5343d","observation_id":"0bb30e1e-15e2-42e3-9614-24962e373b90","resolution":{"observed_at":"2026-07-13T20:27:45.196743Z","resolver_source":null,"status":"malformed_identifier"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1609.07196","last_updated":"2024-05-11T23:37:54Z","snapshot_observed_at":"2026-08-09T19:30:59.179900Z","submitted_at":"2016-09-23T00:35:53Z","title":"Review of multi-fidelity models","version":6},"cited_work":{"arxiv_id":"1609.07196","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"1609.07196","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Review of multi-ﬁdelity models","venue":null,"work_id":"690badb0-8565-42b6-98a9-364a6711161f","year":2016},"citing_paper":{"arxiv_id":"2605.02871","last_updated":"2026-05-04T17:45:47Z","snapshot_observed_at":"2026-08-04T00:05:28.813371Z","submitted_at":"2026-05-04T17:45:47Z","title":"Multi-fidelity surrogates for mechanics of composites: from co-kriging to multi-fidelity neural networks","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-05-08T01:58:11.576425Z"},"links":{"cited_paper":"/paper/1609.07196","citing_paper":"/paper/2605.02871"},"observation_digest":"sha256:1cd0ef310161fafaeeb24f7a81b7e2ffc18d020b91a6938d5187f4dd5b2904ec","observation_id":"3f1d0b4e-f377-4a5a-b748-7a7099a59470","resolution":{"observed_at":"2026-05-11T23:01:15.899128Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1609.07196","last_updated":"2024-05-11T23:37:54Z","snapshot_observed_at":"2026-08-09T19:30:59.179900Z","submitted_at":"2016-09-23T00:35:53Z","title":"Review of multi-fidelity models","version":6},"cited_work":{"arxiv_id":"1609.07196","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"1609.07196","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Review of multi-ﬁdelity models","venue":null,"work_id":"690badb0-8565-42b6-98a9-364a6711161f","year":2016},"citing_paper":{"arxiv_id":"2605.10406","last_updated":"2026-06-06T08:18:07Z","snapshot_observed_at":"2026-08-02T15:39:14.516950Z","submitted_at":"2026-05-11T11:43:38Z","title":"Multi-Fidelity Quantile Regression","version":1},"reference_index":71,"source":"arxiv_source","source_observed_at":"2026-05-12T05:14:15.478876Z"},"links":{"cited_paper":"/paper/1609.07196","citing_paper":"/paper/2605.10406"},"observation_digest":"sha256:f63043cfac9e845895b072aad9e543bf22301f9e75732cb9a84b54879007ceb6","observation_id":"361fab06-9c51-4aaa-b77d-aae656c379a1","resolution":{"observed_at":"2026-05-12T05:16:25.225968Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/1609.07196/citation-record","integrity":"/paper/1609.07196/integrity","json":"/paper/1609.07196/citation-record.json","paper":"/paper/1609.07196"},"outbound":[],"paper":{"arxiv_id":"1609.07196","last_updated":"2024-05-11T23:37:54Z","latest_version":6,"primary_category":"stat.AP","snapshot_observed_at":"2026-08-09T19:30:59.179900Z","submitted_at":"2016-09-23T00:35:53Z","title":"Review of multi-fidelity models"},"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":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"thesis":"As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 7 inbound Pith citation observations for arXiv:1609.07196."}