{"as_of":"2026-08-09T18:13:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:89884481a7df1d9130fd033ea87e8567a87ee364691c3c7b4963fefc2b8c7de5","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":"2026-08-05T17:12:07.617673Z","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":"2026-08-09T06:31:02.800959+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/2509.06966/citation-record","integrity":"/paper/2509.06966/integrity","json":"/paper/2509.06966/citation-record.json","paper":"/paper/2509.06966"},"outbound":[{"citation":{"cited_paper":{"arxiv_id":"2403.07815","last_updated":"2024-11-04T17:42:45Z","snapshot_observed_at":"2026-07-06T17:43:27.034067Z","submitted_at":"2024-03-12T16:53:54Z","title":"Chronos: Learning the Language of Time Series","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2403.07815","snapshot_observed_at":"2026-08-05T17:12:06.419990Z","title":"Chronos: Learning the language of time series","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.06966","last_updated":"2025-08-22T23:22:41Z","snapshot_observed_at":"2026-08-09T05:31:40.318187Z","submitted_at":"2025-08-22T23:22:41Z","title":"Cross-device Zero-shot Label Transfer via Alignment of Time Series Foundation Model Embeddings","version":1},"reference_index":1,"source":"arxiv_source","source_observed_at":"2026-08-05T17:12:06.419990Z"},"links":{"cited_paper":"/paper/2403.07815","citing_paper":"/paper/2509.06966"},"observation_digest":"sha256:450b2401d5c4c4ef5fe80fdafbb7cbd580a19b6aa5497e6a0312cb17f8cb37de","observation_id":"f9075806-ca98-43a9-83eb-f17772c5ff13","resolution":{"observed_at":"2026-08-05T17:12:06.419990Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2003.06505","last_updated":"2020-03-13T23:10:39Z","snapshot_observed_at":"2026-07-06T09:04:37.917150Z","submitted_at":"2020-03-13T23:10:39Z","title":"AutoGluon-Tabular: Robust and Accurate AutoML for Structured Data","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2003.06505","snapshot_observed_at":"2026-08-05T17:12:06.486604Z","title":"Autogluon-tabular: Robust and accurate automl for structured data","venue":null,"work_id":null,"year":2003},"citing_paper":{"arxiv_id":"2509.06966","last_updated":"2025-08-22T23:22:41Z","snapshot_observed_at":"2026-08-09T05:31:40.318187Z","submitted_at":"2025-08-22T23:22:41Z","title":"Cross-device Zero-shot Label Transfer via Alignment of Time Series Foundation Model Embeddings","version":1},"reference_index":2,"source":"arxiv_source","source_observed_at":"2026-08-05T17:12:06.486604Z"},"links":{"cited_paper":"/paper/2003.06505","citing_paper":"/paper/2509.06966"},"observation_digest":"sha256:1ca4c60bd0204409c8cdc3af79295ca14b2325da14a54dacc2fc27886bad4614","observation_id":"5a76761e-7dc5-48c8-859a-371810c39b82","resolution":{"observed_at":"2026-08-05T17:12:06.486604Z","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":"2026-08-05T17:12:06.567836Z","title":"Parameter-efficient transfer learning for nlp","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2509.06966","last_updated":"2025-08-22T23:22:41Z","snapshot_observed_at":"2026-08-09T05:31:40.318187Z","submitted_at":"2025-08-22T23:22:41Z","title":"Cross-device Zero-shot Label Transfer via Alignment of Time Series Foundation Model Embeddings","version":1},"reference_index":3,"source":"arxiv_source","source_observed_at":"2026-08-05T17:12:06.567836Z"},"links":{"citing_paper":"/paper/2509.06966"},"observation_digest":"sha256:10208bea506fe8b8617ee510594b6254bcce5c339be5ffd7940f8709660b2fab","observation_id":"9b43feec-2665-4cdc-89fd-47091e343e6c","resolution":{"observed_at":"2026-08-05T17:12:06.567836Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2311.02695","last_updated":"2024-03-22T17:00:40Z","snapshot_observed_at":"2026-08-09T05:31:47.557698Z","submitted_at":"2023-11-05T16:05:00Z","title":"Identifying Linearly-Mixed Causal Representations from Multi-Node Interventions","version":2},"cited_work":{"arxiv_id":"2311.02695","doi":null,"metadata_source":"pith","pith_arxiv_id":"2311.02695","snapshot_observed_at":"2026-08-05T17:12:07.743105Z","title":"Identifying Linearly-Mixed Causal Representations from Multi-Node Interventions","venue":"stat.ML","work_id":"e2547936-08d2-4769-919b-93941b69c08a","year":2023},"citing_paper":{"arxiv_id":"2509.06966","last_updated":"2025-08-22T23:22:41Z","snapshot_observed_at":"2026-08-09T05:31:40.318187Z","submitted_at":"2025-08-22T23:22:41Z","title":"Cross-device Zero-shot Label Transfer via Alignment of Time Series Foundation Model Embeddings","version":1},"reference_index":4,"source":"arxiv_source","source_observed_at":"2026-08-05T17:12:06.603345Z"},"links":{"cited_paper":"/paper/2311.02695","citing_paper":"/paper/2509.06966"},"observation_digest":"sha256:71b179d479056df15a2ec72dd5cb2c3b0b86d06fafd65cde2155a45fb0bc954a","observation_id":"98d8a48d-31ce-49c0-9b37-ef02e09d2ae7","resolution":{"observed_at":"2026-08-05T17:12:07.748263Z","resolver_source":"local_arxiv","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"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T17:12:07.867022Z","title":"Least squares generative adversarial networks","venue":null,"work_id":"16783916-561b-4c6d-b02a-1fa8a76c8d97","year":2017},"citing_paper":{"arxiv_id":"2509.06966","last_updated":"2025-08-22T23:22:41Z","snapshot_observed_at":"2026-08-09T05:31:40.318187Z","submitted_at":"2025-08-22T23:22:41Z","title":"Cross-device Zero-shot Label Transfer via Alignment of Time Series Foundation Model Embeddings","version":1},"reference_index":5,"source":"arxiv_source","source_observed_at":"2026-08-05T17:12:06.651925Z"},"links":{"citing_paper":"/paper/2509.06966"},"observation_digest":"sha256:ee704e2c8b8cc5ce69391976869347c451b802a261a5f343149dea99dc4c1e74","observation_id":"46479b90-375a-47e9-ac7a-d5d5c28c965c","resolution":{"observed_at":"2026-08-05T17:12:07.872144Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":"2410.13638","last_updated":"2024-10-17T15:08:21Z","snapshot_observed_at":"2026-08-04T15:47:09.454523Z","submitted_at":"2024-10-17T15:08:21Z","title":"Scaling Wearable Foundation Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.13638","snapshot_observed_at":"2026-08-05T17:12:06.804548Z","title":"Scaling wearable foundation models","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.06966","last_updated":"2025-08-22T23:22:41Z","snapshot_observed_at":"2026-08-09T05:31:40.318187Z","submitted_at":"2025-08-22T23:22:41Z","title":"Cross-device Zero-shot Label Transfer via Alignment of Time Series Foundation Model Embeddings","version":1},"reference_index":6,"source":"arxiv_source","source_observed_at":"2026-08-05T17:12:06.804548Z"},"links":{"cited_paper":"/paper/2410.13638","citing_paper":"/paper/2509.06966"},"observation_digest":"sha256:f8acd3340d6220c126c4697575584dc4e8df996915ca78d38faea66acc46d375","observation_id":"f518bc19-36f4-4b72-b433-455dbb236732","resolution":{"observed_at":"2026-08-05T17:12:06.804548Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2303.17289","last_updated":"2024-01-11T08:56:32Z","snapshot_observed_at":"2026-08-09T05:31:46.965895Z","submitted_at":"2023-03-30T10:53:20Z","title":"The strongly regular twisted $D_{5,5}(q)$ graph","version":5},"cited_work":{"arxiv_id":"2303.17289","doi":null,"metadata_source":"pith","pith_arxiv_id":"2303.17289","snapshot_observed_at":"2026-08-05T17:12:07.701950Z","title":"The strongly regular twisted $D_{5,5}(q)$ graph","venue":"math.CO","work_id":"3071f35d-d75e-44c2-b757-a6abbce450f1","year":2023},"citing_paper":{"arxiv_id":"2509.06966","last_updated":"2025-08-22T23:22:41Z","snapshot_observed_at":"2026-08-09T05:31:40.318187Z","submitted_at":"2025-08-22T23:22:41Z","title":"Cross-device Zero-shot Label Transfer via Alignment of Time Series Foundation Model Embeddings","version":1},"reference_index":7,"source":"arxiv_source","source_observed_at":"2026-08-05T17:12:06.928728Z"},"links":{"cited_paper":"/paper/2303.17289","citing_paper":"/paper/2509.06966"},"observation_digest":"sha256:9d299348f4efb06991b7b763ff53e84046aa0df465372fb701f2004bd743efbb","observation_id":"f6bf6ed8-5dcf-4d1a-93d4-c5743f45b6f1","resolution":{"observed_at":"2026-08-05T17:12:07.707092Z","resolver_source":"local_arxiv","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"}},{"citation":{"cited_paper":{"arxiv_id":"1905.10437","last_updated":"2020-02-20T21:08:57Z","snapshot_observed_at":"2026-08-06T09:33:52.442294Z","submitted_at":"2019-05-24T20:28:57Z","title":"N-BEATS: Neural basis expansion analysis for interpretable time series forecasting","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1905.10437","snapshot_observed_at":"2026-08-05T17:12:07.074864Z","title":"N-beats: Neural basis expansion analysis for interpretable time series forecasting","venue":null,"work_id":null,"year":1905},"citing_paper":{"arxiv_id":"2509.06966","last_updated":"2025-08-22T23:22:41Z","snapshot_observed_at":"2026-08-09T05:31:40.318187Z","submitted_at":"2025-08-22T23:22:41Z","title":"Cross-device Zero-shot Label Transfer via Alignment of Time Series Foundation Model Embeddings","version":1},"reference_index":8,"source":"arxiv_source","source_observed_at":"2026-08-05T17:12:07.074864Z"},"links":{"cited_paper":"/paper/1905.10437","citing_paper":"/paper/2509.06966"},"observation_digest":"sha256:37d112fa73ee1f4d7d55d93f2998f8d66bca8d1f9192aa8f46de38853325fb57","observation_id":"8e524f03-e6dc-47f5-8ddd-3a8f6c3aefa1","resolution":{"observed_at":"2026-08-05T17:12:07.074864Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2502.06037","last_updated":"2025-09-10T16:22:20Z","snapshot_observed_at":"2026-08-09T05:31:11.961434Z","submitted_at":"2025-02-09T21:21:55Z","title":"Investigating Compositional Reasoning in Time Series Foundation Models","version":2},"cited_work":{"arxiv_id":"2502.06037","doi":null,"metadata_source":"pith","pith_arxiv_id":"2502.06037","snapshot_observed_at":"2026-08-05T17:12:07.655636Z","title":"Investigating Compositional Reasoning in Time Series Foundation Models","venue":"cs.LG","work_id":"527869f4-beea-4b49-aaf1-fd7f7cba9051","year":2025},"citing_paper":{"arxiv_id":"2509.06966","last_updated":"2025-08-22T23:22:41Z","snapshot_observed_at":"2026-08-09T05:31:40.318187Z","submitted_at":"2025-08-22T23:22:41Z","title":"Cross-device Zero-shot Label Transfer via Alignment of Time Series Foundation Model Embeddings","version":1},"reference_index":9,"source":"arxiv_source","source_observed_at":"2026-08-05T17:12:07.198774Z"},"links":{"cited_paper":"/paper/2502.06037","citing_paper":"/paper/2509.06966"},"observation_digest":"sha256:c9a0e586d999592ba41effa7a440cc990b7eb02b783dc7f885a8d6aa74ce381a","observation_id":"585205d3-849f-4971-9d79-5f007035191f","resolution":{"observed_at":"2026-08-05T17:12:07.663014Z","resolver_source":"local_arxiv","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":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T17:12:07.851251Z","title":"Deep representation learning identifies associations between physical activity and sleep patterns during pregnancy and prematurity","venue":null,"work_id":"7917acc4-20e4-4c9e-8d2c-2b1ccd6c113b","year":2023},"citing_paper":{"arxiv_id":"2509.06966","last_updated":"2025-08-22T23:22:41Z","snapshot_observed_at":"2026-08-09T05:31:40.318187Z","submitted_at":"2025-08-22T23:22:41Z","title":"Cross-device Zero-shot Label Transfer via Alignment of Time Series Foundation Model Embeddings","version":1},"reference_index":10,"source":"arxiv_source","source_observed_at":"2026-08-05T17:12:07.271395Z"},"links":{"citing_paper":"/paper/2509.06966"},"observation_digest":"sha256:7a773981e9577501714c4f73ba03dcd8926936b37c8c52b428de3274f01a1316","observation_id":"7fae7dc2-b98b-4118-8c34-49c9f8daf850","resolution":{"observed_at":"2026-08-05T17:12:07.856162Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T17:12:07.399405Z","title":"Attention is all you need","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2509.06966","last_updated":"2025-08-22T23:22:41Z","snapshot_observed_at":"2026-08-09T05:31:40.318187Z","submitted_at":"2025-08-22T23:22:41Z","title":"Cross-device Zero-shot Label Transfer via Alignment of Time Series Foundation Model Embeddings","version":1},"reference_index":11,"source":"arxiv_source","source_observed_at":"2026-08-05T17:12:07.399405Z"},"links":{"citing_paper":"/paper/2509.06966"},"observation_digest":"sha256:21e46f22cb11ff1097298e714e2629cfa3a3d4729fd2d16132a990b6ff7d12ad","observation_id":"7eff169b-62d9-4141-8973-7c2825fd560f","resolution":{"observed_at":"2026-08-05T17:12:07.399405Z","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":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T17:12:07.824996Z","title":"Comparison of raw accelerometry data from actigraph, apple watch, garmin, and fitbit using a mechanical shaker table","venue":null,"work_id":"93d3585f-e3f7-4782-90e8-673ae60b236a","year":2024},"citing_paper":{"arxiv_id":"2509.06966","last_updated":"2025-08-22T23:22:41Z","snapshot_observed_at":"2026-08-09T05:31:40.318187Z","submitted_at":"2025-08-22T23:22:41Z","title":"Cross-device Zero-shot Label Transfer via Alignment of Time Series Foundation Model Embeddings","version":1},"reference_index":12,"source":"arxiv_source","source_observed_at":"2026-08-05T17:12:07.427058Z"},"links":{"citing_paper":"/paper/2509.06966"},"observation_digest":"sha256:5aedfc24c6b8ae57405833a688663fcb57a55b9467cfcf239db34d73bef6a9d6","observation_id":"cb6e5972-4629-4586-ac48-93335cf03502","resolution":{"observed_at":"2026-08-05T17:12:07.830151Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T17:12:07.809353Z","title":"Ts2vec: Towards universal representation of time series","venue":null,"work_id":"78c8fd9a-a09a-48c7-a8d9-4afd8a2ae5f0","year":2022},"citing_paper":{"arxiv_id":"2509.06966","last_updated":"2025-08-22T23:22:41Z","snapshot_observed_at":"2026-08-09T05:31:40.318187Z","submitted_at":"2025-08-22T23:22:41Z","title":"Cross-device Zero-shot Label Transfer via Alignment of Time Series Foundation Model Embeddings","version":1},"reference_index":13,"source":"arxiv_source","source_observed_at":"2026-08-05T17:12:07.613094Z"},"links":{"citing_paper":"/paper/2509.06966"},"observation_digest":"sha256:4840b6b292e6b7253bede591a4881f8dbe715f8ef88939553064636133062de3","observation_id":"278a1833-16b2-447b-a124-d7c65e9b0c92","resolution":{"observed_at":"2026-08-05T17:12:07.813727Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T17:12:07.793939Z","title":"Informer: Beyond efficient transformer for long sequence time-series forecasting","venue":null,"work_id":"f891d532-e947-4cf7-80f2-bd4cf19cdbb3","year":2021},"citing_paper":{"arxiv_id":"2509.06966","last_updated":"2025-08-22T23:22:41Z","snapshot_observed_at":"2026-08-09T05:31:40.318187Z","submitted_at":"2025-08-22T23:22:41Z","title":"Cross-device Zero-shot Label Transfer via Alignment of Time Series Foundation Model Embeddings","version":1},"reference_index":14,"source":"arxiv_source","source_observed_at":"2026-08-05T17:12:07.617673Z"},"links":{"citing_paper":"/paper/2509.06966"},"observation_digest":"sha256:20fb9667dea376a8326139dd5842dcabba9f3d1e1fcd0656961766aad22acaf4","observation_id":"82762743-d264-4d18-bcf4-eb226e2a67c4","resolution":{"observed_at":"2026-08-05T17:12:07.799075Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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"}}],"paper":{"arxiv_id":"2509.06966","last_updated":"2025-08-22T23:22:41Z","latest_version":1,"primary_category":"eess.SP","snapshot_observed_at":"2026-08-09T05:31:40.318187Z","submitted_at":"2025-08-22T23:22:41Z","title":"Cross-device Zero-shot Label Transfer via Alignment of Time Series Foundation Model Embeddings"},"reference_resolution":{"displayed":14,"state_counts":{"malformed_identifier":0,"metadata_mismatch":2,"parse_uncertain":0,"unresolved":6,"verified_exact":1,"verified_fuzzy":5},"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":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"thesis":"As of 9 August 2026, this Paper Citation Record lists 14 of 14 outbound references and 0 inbound Pith citation observations for arXiv:2509.06966."}