{"as_of":"2026-08-23T09:07:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:0379296120de2ca882d2a9c24817380e93b1373681c249ce8c249b1c9601abe1","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":8,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":8,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-23T06:30:58.430688+00:00","state":"measured"},{"denominator":8,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":8,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-15T20:10:45.846899Z","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":"2026-05-21T06:09:41.688651Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2406.19611","last_updated":"2024-06-28T02:35:05Z","snapshot_observed_at":"2026-08-22T02:33:36.371541Z","submitted_at":"2024-06-28T02:35:05Z","title":"Multimodal Data Integration for Precision Oncology: Challenges and Future Directions","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2406.19611","snapshot_observed_at":"2026-08-12T19:46:10.929225Z","title":"Multimodal data integration for precision oncology: Challenges and future directions","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2411.10356","last_updated":"2024-11-15T17:05:33Z","snapshot_observed_at":"2026-08-18T19:20:55.681124Z","submitted_at":"2024-11-15T17:05:33Z","title":"Weakly-Supervised Multimodal Learning on MIMIC-CXR","version":1},"reference_index":21,"source":"arxiv_source","source_observed_at":"2026-08-12T19:46:10.929225Z"},"links":{"cited_paper":"/paper/2406.19611","citing_paper":"/paper/2411.10356"},"observation_digest":"sha256:3c9d528961d59b966c3017912890cc1848c85ac9bfa4bd0f71bb9003e0801f38","observation_id":"02c95a41-181b-4c89-9692-be4986831fe4","resolution":{"observed_at":"2026-08-12T19:46:10.929225Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2406.19611","last_updated":"2024-06-28T02:35:05Z","snapshot_observed_at":"2026-08-22T02:33:36.371541Z","submitted_at":"2024-06-28T02:35:05Z","title":"Multimodal Data Integration for Precision Oncology: Challenges and Future Directions","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2406.19611","snapshot_observed_at":"2026-08-10T00:29:01.981215Z","title":"Multi- modal data integration for precision oncology: Challenges and future directions","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2501.18170","last_updated":"2025-02-01T03:19:00Z","snapshot_observed_at":"2026-08-13T09:25:21.364460Z","submitted_at":"2025-01-30T06:49:57Z","title":"Continually Evolved Multimodal Foundation Models for Cancer Prognosis","version":2},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-10T00:29:01.981215Z"},"links":{"cited_paper":"/paper/2406.19611","citing_paper":"/paper/2501.18170"},"observation_digest":"sha256:980d1740cfd2405baf288ea74bacc52c6f077f9d08ef1a96cf4ee71389ca4c02","observation_id":"4d766529-bb35-472a-96ba-bde3858e1c45","resolution":{"observed_at":"2026-08-10T00:29:01.981215Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2406.19611","last_updated":"2024-06-28T02:35:05Z","snapshot_observed_at":"2026-08-22T02:33:36.371541Z","submitted_at":"2024-06-28T02:35:05Z","title":"Multimodal Data Integration for Precision Oncology: Challenges and Future Directions","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2406.19611","snapshot_observed_at":"2026-08-15T20:10:45.846899Z","title":"arXiv preprint arXiv:2406.19611 (2024)","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.13940","last_updated":"2025-07-28T08:10:33Z","snapshot_observed_at":"2026-08-15T20:04:58.490290Z","submitted_at":"2025-05-20T05:18:15Z","title":"DrugPilot: LLM-based Parameterized Reasoning Agent for Drug Discovery","version":2},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-08-15T20:10:45.846899Z"},"links":{"cited_paper":"/paper/2406.19611","citing_paper":"/paper/2505.13940"},"observation_digest":"sha256:4ed31a0a0ee4ad6f24286c8ecb405696644472bbccfc501e0daa3196cee42e28","observation_id":"6db728dd-8533-4255-a265-0624e9a2ee7e","resolution":{"observed_at":"2026-08-15T20:10:45.846899Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2406.19611","last_updated":"2024-06-28T02:35:05Z","snapshot_observed_at":"2026-08-22T02:33:36.371541Z","submitted_at":"2024-06-28T02:35:05Z","title":"Multimodal Data Integration for Precision Oncology: Challenges and Future Directions","version":1},"cited_work":{"arxiv_id":"2406.19611","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2406.19611","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Multimodal data integration for precision oncology: Challenges and future directions","venue":null,"work_id":"d532f42c-09dd-4186-8451-9e131018e22e","year":2024},"citing_paper":{"arxiv_id":"2507.09028","last_updated":"2025-12-18T21:46:44Z","snapshot_observed_at":"2026-08-15T17:54:45.238126Z","submitted_at":"2025-07-11T21:23:21Z","title":"From Classical Machine Learning to Emerging Foundation Models: Review on Multimodal Data Integration for Cancer Research","version":2},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-05-19T05:10:23.963494Z"},"links":{"cited_paper":"/paper/2406.19611","citing_paper":"/paper/2507.09028"},"observation_digest":"sha256:883484ebc92d042508714cfb91c6ad7f091bf6f6e966a8067c8bdb933ea63e9c","observation_id":"8376e46b-1551-4512-935c-81fcda67ab3d","resolution":{"observed_at":"2026-05-19T05:12:05.158852Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2406.19611","last_updated":"2024-06-28T02:35:05Z","snapshot_observed_at":"2026-08-22T02:33:36.371541Z","submitted_at":"2024-06-28T02:35:05Z","title":"Multimodal Data Integration for Precision Oncology: Challenges and Future Directions","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2406.19611","snapshot_observed_at":"2026-08-04T16:15:39.917703Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.15017","last_updated":"2026-06-06T07:26:43Z","snapshot_observed_at":"2026-08-12T22:13:34.243250Z","submitted_at":"2025-09-18T14:47:20Z","title":"No Modality Left Behind: Adapting to Missing Modalities via Knowledge Distillation for Brain Tumor Segmentation","version":2},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-04T16:15:39.917703Z"},"links":{"cited_paper":"/paper/2406.19611","citing_paper":"/paper/2509.15017"},"observation_digest":"sha256:24283e99b68f9f109a5073c4ab549ee17ecd40535f0fc3aa034360de3a2ce5bd","observation_id":"73d77b8c-1683-4c76-b8aa-a3128775a84c","resolution":{"observed_at":"2026-08-04T16:15:39.917703Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2406.19611","last_updated":"2024-06-28T02:35:05Z","snapshot_observed_at":"2026-08-22T02:33:36.371541Z","submitted_at":"2024-06-28T02:35:05Z","title":"Multimodal Data Integration for Precision Oncology: Challenges and Future Directions","version":1},"cited_work":{"arxiv_id":"2406.19611","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2406.19611","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Multimodal data integration for precision oncology: Challenges and future directions","venue":null,"work_id":"d532f42c-09dd-4186-8451-9e131018e22e","year":2024},"citing_paper":{"arxiv_id":"2605.20891","last_updated":"2026-05-20T08:31:09Z","snapshot_observed_at":"2026-08-14T19:48:26.874751Z","submitted_at":"2026-05-20T08:31:09Z","title":"HDMoE: A Hierarchical Decoupling-Fusion Mixture-of-Experts Framework for Multimodal Cancer Survival Prediction","version":1},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-05-21T06:05:19.340581Z"},"links":{"cited_paper":"/paper/2406.19611","citing_paper":"/paper/2605.20891"},"observation_digest":"sha256:c18072cd7a2e1bee97308fd46f19562e163f9b9acc4b0dd430042c584a4980cb","observation_id":"edb97b9b-d920-49a3-be5e-7b18f38a56a1","resolution":{"observed_at":"2026-05-21T06:09:41.691108Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2406.19611","last_updated":"2024-06-28T02:35:05Z","snapshot_observed_at":"2026-08-22T02:33:36.371541Z","submitted_at":"2024-06-28T02:35:05Z","title":"Multimodal Data Integration for Precision Oncology: Challenges and Future Directions","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2406.19611","snapshot_observed_at":"2026-08-01T19:37:05.378308Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.16916","last_updated":"2026-07-18T18:16:44Z","snapshot_observed_at":"2026-08-22T02:33:48.019371Z","submitted_at":"2026-07-18T18:16:44Z","title":"Enhancing Personalized Bladder Cancer Treatment Through Reinforcement Learning: A Recurrent Patient State Transition Decision Support Framework","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-01T19:37:05.378308Z"},"links":{"cited_paper":"/paper/2406.19611","citing_paper":"/paper/2607.16916"},"observation_digest":"sha256:6cc2f8a917c544ba7e4a6f5134f94db3797aca76fdc18d396a3961663156f3e5","observation_id":"78345f6f-d6cd-421c-ab56-d2764cb54fa4","resolution":{"observed_at":"2026-08-01T19:37:05.378308Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2406.19611","last_updated":"2024-06-28T02:35:05Z","snapshot_observed_at":"2026-08-22T02:33:36.371541Z","submitted_at":"2024-06-28T02:35:05Z","title":"Multimodal Data Integration for Precision Oncology: Challenges and Future Directions","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2406.19611","snapshot_observed_at":"2026-08-05T22:41:26.125032Z","title":"Multimodal data integration for precision oncology: Challenges and future directions.arXiv preprint arXiv:2406.19611, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2608.03247","last_updated":"2026-08-04T07:19:53Z","snapshot_observed_at":"2026-08-22T02:33:49.595022Z","submitted_at":"2026-08-04T07:19:53Z","title":"CIGTSurv: Clinical Information Guided Tri-modal Survival Prediction with Local Prototype Association and Global Feature Alignment","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-05T22:41:26.125032Z"},"links":{"cited_paper":"/paper/2406.19611","citing_paper":"/paper/2608.03247"},"observation_digest":"sha256:e183a86a2b178b841d15c050e6b2dcab08ec2ef403ada685461b4f3474301584","observation_id":"96f7caf1-fd12-403f-b3c6-595a24fc47cc","resolution":{"observed_at":"2026-08-05T22:41:26.125032Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2406.19611/citation-record","integrity":"/paper/2406.19611/integrity","json":"/paper/2406.19611/citation-record.json","paper":"/paper/2406.19611"},"outbound":[],"paper":{"arxiv_id":"2406.19611","last_updated":"2024-06-28T02:35:05Z","latest_version":1,"primary_category":"q-bio.QM","snapshot_observed_at":"2026-08-22T02:33:36.371541Z","submitted_at":"2024-06-28T02:35:05Z","title":"Multimodal Data Integration for Precision Oncology: Challenges and Future Directions"},"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":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"thesis":"As of 23 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 8 inbound Pith citation observations for arXiv:2406.19611."}