{"as_of":"2026-08-08T09:32:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:c0a85dcbd0ccbb4016788cdcd117d12d986cfc09b02f7a884d8edb2faa04e79c","coverage":[{"denominator":16,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":16,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T13:51:15.425104Z","state":"measured"},{"denominator":16,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":16,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-08T06:32:00.761636+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/2505.20876/citation-record","integrity":"/paper/2505.20876/integrity","json":"/paper/2505.20876/citation-record.json","paper":"/paper/2505.20876"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:51:18.658606Z","title":null,"venue":null,"work_id":"733a76e2-e361-4faf-8073-76149cd7998e","year":2009},"citing_paper":{"arxiv_id":"2505.20876","last_updated":"2025-05-29T09:22:04Z","snapshot_observed_at":"2026-08-07T13:43:12.136757Z","submitted_at":"2025-05-27T08:24:17Z","title":"Stereo Radargrammetry Using Deep Learning from Airborne SAR Images","version":3},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-07T13:51:13.830206Z"},"links":{"citing_paper":"/paper/2505.20876"},"observation_digest":"sha256:3ddb6f8f722fa28f5c9b63a1d70bfef3af695286a2bbdb1e86a9e17ffa98c168","observation_id":"dd545810-19f4-440a-97d1-16b78b29cb4f","resolution":{"observed_at":"2026-08-07T13:51:18.800374Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"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"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:51:18.419585Z","title":"Kerle, Encyclopedia of Natural Hazards","venue":null,"work_id":"3484067f-15b7-4b93-bf0b-c109af562710","year":2013},"citing_paper":{"arxiv_id":"2505.20876","last_updated":"2025-05-29T09:22:04Z","snapshot_observed_at":"2026-08-07T13:43:12.136757Z","submitted_at":"2025-05-27T08:24:17Z","title":"Stereo Radargrammetry Using Deep Learning from Airborne SAR Images","version":3},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-07T13:51:13.942498Z"},"links":{"citing_paper":"/paper/2505.20876"},"observation_digest":"sha256:62cb141b1fe2504ddf0d364450faa89123c6a08bba3e918e341fea069cef28a6","observation_id":"f6eef04d-7f94-4d4c-afd2-e739cad2495c","resolution":{"observed_at":"2026-08-07T13:51:18.522875Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"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"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:51:18.270500Z","title":"Stereo radargrammetry using airborne SAR images wit h- out GCP,","venue":null,"work_id":"a6a99147-cad8-40c4-b931-b4ff388bc60b","year":2015},"citing_paper":{"arxiv_id":"2505.20876","last_updated":"2025-05-29T09:22:04Z","snapshot_observed_at":"2026-08-07T13:43:12.136757Z","submitted_at":"2025-05-27T08:24:17Z","title":"Stereo Radargrammetry Using Deep Learning from Airborne SAR Images","version":3},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-07T13:51:14.007441Z"},"links":{"citing_paper":"/paper/2505.20876"},"observation_digest":"sha256:66e6bc36106e0ab0f220aaf010f100de1cfb89709a2fd9dffa80490fdb202561","observation_id":"dcfafbbc-8fa3-4bd0-bdfc-0e47cdec5ddc","resolution":{"observed_at":"2026-08-07T13:51:18.325621Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"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"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:51:18.043174Z","title":"Elevation measurement from single-pass SAR images,","venue":null,"work_id":"1cb6f26a-2975-44cb-ac73-ea4af5e39d64","year":2017},"citing_paper":{"arxiv_id":"2505.20876","last_updated":"2025-05-29T09:22:04Z","snapshot_observed_at":"2026-08-07T13:43:12.136757Z","submitted_at":"2025-05-27T08:24:17Z","title":"Stereo Radargrammetry Using Deep Learning from Airborne SAR Images","version":3},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-07T13:51:14.085179Z"},"links":{"citing_paper":"/paper/2505.20876"},"observation_digest":"sha256:17abc421ed8861d3fe677406b7aeb97bdcd9f736d6b6348a89e9b9f57f670179","observation_id":"91aa4f2d-60c4-4d1c-ba83-d0bceed18649","resolution":{"observed_at":"2026-08-07T13:51:18.145900Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"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"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:51:17.796391Z","title":"Towards on-board elevation measurement using interferom etry and radargrammetry from single-pass SAR images,","venue":null,"work_id":"012eb607-13fa-4831-8383-9fff37015993","year":2018},"citing_paper":{"arxiv_id":"2505.20876","last_updated":"2025-05-29T09:22:04Z","snapshot_observed_at":"2026-08-07T13:43:12.136757Z","submitted_at":"2025-05-27T08:24:17Z","title":"Stereo Radargrammetry Using Deep Learning from Airborne SAR Images","version":3},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-07T13:51:14.225027Z"},"links":{"citing_paper":"/paper/2505.20876"},"observation_digest":"sha256:22a897f5bdde861771e418744a5e5ed7754674fd7fcc6fa91ae1892c3d223cb8","observation_id":"179efea0-71ac-4317-9189-55f5d6bab718","resolution":{"observed_at":"2026-08-07T13:51:17.917148Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"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"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:51:17.613260Z","title":"Accurate 3D measurement from two SAR images without prior knowledge of scene,","venue":null,"work_id":"b1f480f3-c690-40f3-9e4a-4ff0df0caeab","year":2021},"citing_paper":{"arxiv_id":"2505.20876","last_updated":"2025-05-29T09:22:04Z","snapshot_observed_at":"2026-08-07T13:43:12.136757Z","submitted_at":"2025-05-27T08:24:17Z","title":"Stereo Radargrammetry Using Deep Learning from Airborne SAR Images","version":3},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-07T13:51:14.319395Z"},"links":{"citing_paper":"/paper/2505.20876"},"observation_digest":"sha256:dc0c57ff67b7428a1252e92c64619dc78121bca23dddc4eca067bae171f12f34","observation_id":"f78081fd-3912-46b8-892f-7c66c0c745c1","resolution":{"observed_at":"2026-08-07T13:51:17.691550Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"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"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:51:17.420046Z","title":"Maˆ ıtre, Processing of Synthetic Aperture Radar Images","venue":null,"work_id":"3b337648-7f3b-4c0b-84ed-8b90594fbc71","year":2010},"citing_paper":{"arxiv_id":"2505.20876","last_updated":"2025-05-29T09:22:04Z","snapshot_observed_at":"2026-08-07T13:43:12.136757Z","submitted_at":"2025-05-27T08:24:17Z","title":"Stereo Radargrammetry Using Deep Learning from Airborne SAR Images","version":3},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-07T13:51:14.401164Z"},"links":{"citing_paper":"/paper/2505.20876"},"observation_digest":"sha256:9152398545c70da4d580fa4c0b0ba05fbb3d3e3b51176754a2bd9b5c854214f1","observation_id":"1606e54d-812a-4b0f-93df-83aa928a1147","resolution":{"observed_at":"2026-08-07T13:51:17.514221Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"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"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:51:17.189513Z","title":"Synthetic aperture radar interferometr y,","venue":null,"work_id":"8cbbca9b-c044-424b-bf43-92c32f455265","year":2000},"citing_paper":{"arxiv_id":"2505.20876","last_updated":"2025-05-29T09:22:04Z","snapshot_observed_at":"2026-08-07T13:43:12.136757Z","submitted_at":"2025-05-27T08:24:17Z","title":"Stereo Radargrammetry Using Deep Learning from Airborne SAR Images","version":3},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-07T13:51:14.471419Z"},"links":{"citing_paper":"/paper/2505.20876"},"observation_digest":"sha256:edea36082b22ca4056a125f5f451b936d0d65082638c40109a1dc49d1e173cc2","observation_id":"b18f3654-6ce4-4a2b-b639-5a6b8cfde43d","resolution":{"observed_at":"2026-08-07T13:51:17.299378Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"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"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:51:16.957899Z","title":"A sub-pixe l cor- respondence search technique for computer vision applicat ions,","venue":null,"work_id":"7bdb0b59-68d1-43f7-b6c5-e9c9261529ca","year":1913},"citing_paper":{"arxiv_id":"2505.20876","last_updated":"2025-05-29T09:22:04Z","snapshot_observed_at":"2026-08-07T13:43:12.136757Z","submitted_at":"2025-05-27T08:24:17Z","title":"Stereo Radargrammetry Using Deep Learning from Airborne SAR Images","version":3},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-07T13:51:14.592126Z"},"links":{"citing_paper":"/paper/2505.20876"},"observation_digest":"sha256:bf7f667ea92d1aa04fae33b46af5d675db2c594e32b2b2bbe2ac67e4e8882453","observation_id":"1329bcb6-d9ee-44d6-8490-88c1de74e5dd","resolution":{"observed_at":"2026-08-07T13:51:17.071100Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"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"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:51:16.765031Z","title":"DKM: Dense kernelized feature matching for geometry esti- mation,","venue":null,"work_id":"b2221e7d-7978-4f12-934a-1d72f9709a72","year":2023},"citing_paper":{"arxiv_id":"2505.20876","last_updated":"2025-05-29T09:22:04Z","snapshot_observed_at":"2026-08-07T13:43:12.136757Z","submitted_at":"2025-05-27T08:24:17Z","title":"Stereo Radargrammetry Using Deep Learning from Airborne SAR Images","version":3},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-07T13:51:14.668465Z"},"links":{"citing_paper":"/paper/2505.20876"},"observation_digest":"sha256:200c519a991dde8287623acefc34e6f5c8d251d6509f1c6126a3c5976f406ed6","observation_id":"6102af80-dbb6-4806-815f-38fb648f8d17","resolution":{"observed_at":"2026-08-07T13:51:16.854621Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"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"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:51:16.533119Z","title":"RoMa: Robust dense feature matching,","venue":null,"work_id":"427d10f6-5294-457a-ad44-4ed08670f142","year":2024},"citing_paper":{"arxiv_id":"2505.20876","last_updated":"2025-05-29T09:22:04Z","snapshot_observed_at":"2026-08-07T13:43:12.136757Z","submitted_at":"2025-05-27T08:24:17Z","title":"Stereo Radargrammetry Using Deep Learning from Airborne SAR Images","version":3},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-07T13:51:14.744127Z"},"links":{"citing_paper":"/paper/2505.20876"},"observation_digest":"sha256:95561a624833bee006906b8d9defd41d9590ad044838bcd0e972ed3f1f24f6c2","observation_id":"8f807dc2-a535-48b6-a6d5-ce7a747f0c44","resolution":{"observed_at":"2026-08-07T13:51:16.626638Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"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"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:51:16.374049Z","title":"V ali dation of ’AW3D’ global DSM generated from ALOS PRISM,","venue":null,"work_id":"971b83e2-2d3a-4d46-8b10-ab6c7dcec866","year":2016},"citing_paper":{"arxiv_id":"2505.20876","last_updated":"2025-05-29T09:22:04Z","snapshot_observed_at":"2026-08-07T13:43:12.136757Z","submitted_at":"2025-05-27T08:24:17Z","title":"Stereo Radargrammetry Using Deep Learning from Airborne SAR Images","version":3},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-07T13:51:14.887723Z"},"links":{"citing_paper":"/paper/2505.20876"},"observation_digest":"sha256:4e2dfe33e7224e5c6c53a91db05efadb45115d3488ad64dc30fe5ff65109c5fe","observation_id":"15b4679d-f8b2-465f-9447-c1e49c13f71a","resolution":{"observed_at":"2026-08-07T13:51:16.437828Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"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"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:51:16.153629Z","title":"Development of X-band airborne polarimetric and interfer o- metric SAR with submeter spatial resolution,","venue":null,"work_id":"ec8c1d2b-f985-490e-907c-7deb3e7e9de4","year":2009},"citing_paper":{"arxiv_id":"2505.20876","last_updated":"2025-05-29T09:22:04Z","snapshot_observed_at":"2026-08-07T13:43:12.136757Z","submitted_at":"2025-05-27T08:24:17Z","title":"Stereo Radargrammetry Using Deep Learning from Airborne SAR Images","version":3},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-07T13:51:15.041691Z"},"links":{"citing_paper":"/paper/2505.20876"},"observation_digest":"sha256:c863cde624755ef2c1eb93031730a16e80c728c9bcd56f4bde05d07d529060ca","observation_id":"c9721b62-3280-47f2-9bbd-5781e124044c","resolution":{"observed_at":"2026-08-07T13:51:16.280668Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"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"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:51:15.943631Z","title":"DINOv2: Learning robust visual features without supervis ion,","venue":null,"work_id":"70d86e70-3250-4328-88e7-ed7351b77d5c","year":2024},"citing_paper":{"arxiv_id":"2505.20876","last_updated":"2025-05-29T09:22:04Z","snapshot_observed_at":"2026-08-07T13:43:12.136757Z","submitted_at":"2025-05-27T08:24:17Z","title":"Stereo Radargrammetry Using Deep Learning from Airborne SAR Images","version":3},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-07T13:51:15.144595Z"},"links":{"citing_paper":"/paper/2505.20876"},"observation_digest":"sha256:81b6b0984dda4158715360a877fd8b2fee9174448ff07bd158d147bc2c165c5f","observation_id":"6ee3e06e-6f6d-44ba-b4c9-f28e73e8f692","resolution":{"observed_at":"2026-08-07T13:51:16.026810Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"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"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:51:15.755455Z","title":"V ery deep convolutional net works for large-scale image recognition,","venue":null,"work_id":"09e4978b-ca2a-4ea0-b6d8-a1f5ecbf16e4","year":2015},"citing_paper":{"arxiv_id":"2505.20876","last_updated":"2025-05-29T09:22:04Z","snapshot_observed_at":"2026-08-07T13:43:12.136757Z","submitted_at":"2025-05-27T08:24:17Z","title":"Stereo Radargrammetry Using Deep Learning from Airborne SAR Images","version":3},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-07T13:51:15.275813Z"},"links":{"citing_paper":"/paper/2505.20876"},"observation_digest":"sha256:038d9bfbe206b54daa47d85c6b59cb4abb9f48ac558a29ec3d323143ad7d44bc","observation_id":"95d7a35a-533e-4945-b034-194eab89a106","resolution":{"observed_at":"2026-08-07T13:51:15.871475Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"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"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:51:15.564771Z","title":"MegaDepth: Learning single-view depth prediction from internet photos,","venue":null,"work_id":"ea7df1d6-04cc-4157-b802-6706e3607b30","year":2018},"citing_paper":{"arxiv_id":"2505.20876","last_updated":"2025-05-29T09:22:04Z","snapshot_observed_at":"2026-08-07T13:43:12.136757Z","submitted_at":"2025-05-27T08:24:17Z","title":"Stereo Radargrammetry Using Deep Learning from Airborne SAR Images","version":3},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-07T13:51:15.425104Z"},"links":{"citing_paper":"/paper/2505.20876"},"observation_digest":"sha256:8f628795eea1dc99f5154029ab097248112f5ca77146a496b814a066c31caf12","observation_id":"a3ead743-4dd8-4e0d-a847-e5adf9dd22ec","resolution":{"observed_at":"2026-08-07T13:51:15.643567Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"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"}],"state":"measured"}}],"paper":{"arxiv_id":"2505.20876","last_updated":"2025-05-29T09:22:04Z","latest_version":3,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-07T13:43:12.136757Z","submitted_at":"2025-05-27T08:24:17Z","title":"Stereo Radargrammetry Using Deep Learning from Airborne SAR Images"},"reference_resolution":{"displayed":16,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":1,"verified_exact":0,"verified_fuzzy":15},"total_outbound_references":16},"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 16 of 16 outbound references and 0 inbound Pith citation observations for arXiv:2505.20876."}