{"as_of":"2026-08-08T20:05:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:8391621fc605047cedfb2ce7a508ea185d27e6a94fa0fc1e08f32e7d34f4312c","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":1,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":1,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-08T06:32:00.761636+00:00","state":"measured"},{"denominator":1,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":1,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-04T11:17:36.261769Z","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":[{"citation":{"cited_paper":{"arxiv_id":"2410.18108","last_updated":"2024-10-08T20:27:11Z","snapshot_observed_at":"2026-07-06T19:38:39.889993Z","submitted_at":"2024-10-08T20:27:11Z","title":"A Deep Learning Approach to Estimate Canopy Height and Uncertainty by Integrating Seasonal Optical, SAR and Limited GEDI LiDAR Data over Northern Forests","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.18108","snapshot_observed_at":"2026-08-04T11:17:36.261769Z","title":"A Deep Learning Approach to Estimate Canopy Height and Uncertainty by Integrating Seasonal Optical, SAR and Limited GEDI LiDAR Data over Northern Forests [Internet]","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2510.06299","last_updated":"2025-10-07T14:29:37Z","snapshot_observed_at":"2026-08-07T17:29:52.545790Z","submitted_at":"2025-10-07T14:29:37Z","title":"Scalable deep fusion of spaceborne lidar and synthetic aperture radar for global forest structural complexity mapping","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-04T11:17:36.261769Z"},"links":{"cited_paper":"/paper/2410.18108","citing_paper":"/paper/2510.06299"},"observation_digest":"sha256:acbbb9bd90b8055808e6f2e88e732e4dc3d66bd0d1d2883d774998e05d569e4c","observation_id":"b5921781-2b88-4676-a459-cd1915bcc9c1","resolution":{"observed_at":"2026-08-04T11:17:36.261769Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2410.18108/citation-record","integrity":"/paper/2410.18108/integrity","json":"/paper/2410.18108/citation-record.json","paper":"/paper/2410.18108"},"outbound":[],"paper":{"arxiv_id":"2410.18108","last_updated":"2024-10-08T20:27:11Z","latest_version":1,"primary_category":"cs.CV","snapshot_observed_at":"2026-07-06T19:38:39.889993Z","submitted_at":"2024-10-08T20:27:11Z","title":"A Deep Learning Approach to Estimate Canopy Height and Uncertainty by Integrating Seasonal Optical, SAR and Limited GEDI LiDAR Data over Northern Forests"},"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":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"thesis":"As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 1 inbound Pith citation observation for arXiv:2410.18108."}