{"as_of":"2026-08-11T19:51:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:acf49c74ae5bf7a43b6644f6bf56c1201781fef49caf0d29f2fae95eef28f078","coverage":[{"denominator":37,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":37,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-09T12:32:31.588566Z","state":"measured"},{"denominator":37,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":37,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-11T06:34:44.6726+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/2502.02624/citation-record","integrity":"/paper/2502.02624/integrity","json":"/paper/2502.02624/citation-record.json","paper":"/paper/2502.02624"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T12:32:31.475280Z","title":"First-of-a-kind muography for nuclear waste characterization","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2502.02624","last_updated":"2025-04-02T08:33:01Z","snapshot_observed_at":"2026-08-09T18:43:30.130567Z","submitted_at":"2025-02-04T14:37:37Z","title":"Muographic Image Upsampling with Machine Learning for Built Infrastructure Applications","version":2},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-09T12:32:31.475280Z"},"links":{"citing_paper":"/paper/2502.02624"},"observation_digest":"sha256:a9c91ef38ec699f3a247fa130816e31facf943fe7a807a768d9654405f1ef6e4","observation_id":"ceee8d3d-6d14-4b2a-aecc-a3f74606eae9","resolution":{"observed_at":"2026-08-09T12:32:31.475280Z","resolver_source":null,"status":"malformed_identifier"},"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":"2026-08-09T12:32:31.478953Z","title":"Cosmic-Ray Tomography for Border Security","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2502.02624","last_updated":"2025-04-02T08:33:01Z","snapshot_observed_at":"2026-08-09T18:43:30.130567Z","submitted_at":"2025-02-04T14:37:37Z","title":"Muographic Image Upsampling with Machine Learning for Built Infrastructure Applications","version":2},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-09T12:32:31.478953Z"},"links":{"citing_paper":"/paper/2502.02624"},"observation_digest":"sha256:bf9f5c8ef9db8170afac80d3d1d4507a22abb03cec506b40cce5228ecb668de5","observation_id":"2724186b-96f7-4c98-840f-b2688e1958a8","resolution":{"observed_at":"2026-08-09T12:32:31.478953Z","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":"2026-08-09T12:32:31.482688Z","title":"Applications of Muography to the Industrial Sector.J","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2502.02624","last_updated":"2025-04-02T08:33:01Z","snapshot_observed_at":"2026-08-09T18:43:30.130567Z","submitted_at":"2025-02-04T14:37:37Z","title":"Muographic Image Upsampling with Machine Learning for Built Infrastructure Applications","version":2},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-09T12:32:31.482688Z"},"links":{"citing_paper":"/paper/2502.02624"},"observation_digest":"sha256:8e857ecc5fee2da96d7ec163a142f58825cc6813a3d34798dd4e356633eac17f","observation_id":"75080449-6d32-49cb-8c8b-63301e69f77f","resolution":{"observed_at":"2026-08-09T12:32:31.482688Z","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":"10.1088/1361-6501/ab00d7","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T05:30:23.456663Z","title":"Cosmic ray tracking to monitor the stability of historical buildings: A feasibility study","venue":"Measurement Science and Technology","work_id":"c5e696a6-0518-4b8d-8ac7-7d414b6965dd","year":2019},"citing_paper":{"arxiv_id":"2502.02624","last_updated":"2025-04-02T08:33:01Z","snapshot_observed_at":"2026-08-09T18:43:30.130567Z","submitted_at":"2025-02-04T14:37:37Z","title":"Muographic Image Upsampling with Machine Learning for Built Infrastructure Applications","version":2},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-09T12:32:31.486798Z"},"links":{"citing_paper":"/paper/2502.02624"},"observation_digest":"sha256:954b9c2e679a3abc2729242bcaaed76134dce40142badb1e778b929db68b0b77","observation_id":"ae1700e3-5bea-4daa-ab51-9024e6dfdc68","resolution":{"observed_at":"2026-08-09T12:32:31.757317Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1007/s10921-021-00797-3","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T05:30:23.456663Z","title":"Muon Tomography of the Interior of a Reinforced Concrete Block: First Experimental Proof of Concept","venue":"Journal of Nondestructive Evaluation","work_id":"90f59368-b8cf-4487-be50-9f76c008a81b","year":2021},"citing_paper":{"arxiv_id":"2502.02624","last_updated":"2025-04-02T08:33:01Z","snapshot_observed_at":"2026-08-09T18:43:30.130567Z","submitted_at":"2025-02-04T14:37:37Z","title":"Muographic Image Upsampling with Machine Learning for Built Infrastructure Applications","version":2},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-09T12:32:31.490384Z"},"links":{"citing_paper":"/paper/2502.02624"},"observation_digest":"sha256:d722932bca0f1df153946bf437eac748dc12b1fc68ae6a38efcfa446f5576732","observation_id":"aac042f2-1192-4a2f-919e-b30d2f38c0f6","resolution":{"observed_at":"2026-08-09T12:32:31.747724Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-09T12:32:31.496485Z","title":"Statistical Reconstruction for Cosmic Ray Muon Tomography","venue":null,"work_id":null,"year":2007},"citing_paper":{"arxiv_id":"2502.02624","last_updated":"2025-04-02T08:33:01Z","snapshot_observed_at":"2026-08-09T18:43:30.130567Z","submitted_at":"2025-02-04T14:37:37Z","title":"Muographic Image Upsampling with Machine Learning for Built Infrastructure Applications","version":2},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-09T12:32:31.496485Z"},"links":{"citing_paper":"/paper/2502.02624"},"observation_digest":"sha256:cde190e88429cbd7ad4247f1e92cb9dec89bc243db967fff9e70533474f0f6f9","observation_id":"6ea34788-78d9-4689-bbe3-a631970eaec2","resolution":{"observed_at":"2026-08-09T12:32:31.496485Z","resolver_source":null,"status":"malformed_identifier"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2405.10417","last_updated":"2024-05-16T19:37:50Z","snapshot_observed_at":"2026-08-09T18:43:02.484727Z","submitted_at":"2024-05-16T19:37:50Z","title":"Cosmic rays for imaging cultural heritage objects","version":1},"cited_work":{"arxiv_id":"2405.10417","doi":"10.48550/arxiv.2405.10417","metadata_source":"pith","pith_arxiv_id":"2405.10417","snapshot_observed_at":"2026-08-10T05:30:23.456663Z","title":"Cosmic rays for imaging cultural heritage objects","venue":"physics.soc-ph","work_id":"1ca14aa4-b54b-436a-9acf-86fcd35ff821","year":2024},"citing_paper":{"arxiv_id":"2502.02624","last_updated":"2025-04-02T08:33:01Z","snapshot_observed_at":"2026-08-09T18:43:30.130567Z","submitted_at":"2025-02-04T14:37:37Z","title":"Muographic Image Upsampling with Machine Learning for Built Infrastructure Applications","version":2},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-09T12:32:31.500090Z"},"links":{"cited_paper":"/paper/2405.10417","citing_paper":"/paper/2502.02624"},"observation_digest":"sha256:fb9ee3d90c5157b46b62c1405578eba7d44e6f127cbcd508ca52827549c96ee3","observation_id":"db551737-8935-4ab2-afab-8da4538a1e67","resolution":{"observed_at":"2026-08-09T12:32:31.737946Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.3390/instruments6040077","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T05:30:23.456663Z","title":"Muography for Inspection of Civil Structures","venue":"Instruments","work_id":"534cd1e1-ed51-47ea-9c7a-0e175a0ac369","year":2022},"citing_paper":{"arxiv_id":"2502.02624","last_updated":"2025-04-02T08:33:01Z","snapshot_observed_at":"2026-08-09T18:43:30.130567Z","submitted_at":"2025-02-04T14:37:37Z","title":"Muographic Image Upsampling with Machine Learning for Built Infrastructure Applications","version":2},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-09T12:32:31.503743Z"},"links":{"citing_paper":"/paper/2502.02624"},"observation_digest":"sha256:6dba6af8fd4261409450ec6d85d28389d8ec39618780beb2ec959d55e3fd9471","observation_id":"e188d236-ac4d-433c-88c7-f0804289413f","resolution":{"observed_at":"2026-08-09T12:32:31.725205Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-09T12:32:31.506227Z","title":"MedGAN: Medical image translation using GANs","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2502.02624","last_updated":"2025-04-02T08:33:01Z","snapshot_observed_at":"2026-08-09T18:43:30.130567Z","submitted_at":"2025-02-04T14:37:37Z","title":"Muographic Image Upsampling with Machine Learning for Built Infrastructure Applications","version":2},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-09T12:32:31.506227Z"},"links":{"citing_paper":"/paper/2502.02624"},"observation_digest":"sha256:fca7e87f1f9101470da1e0524c3eb6a2a71bf9b1d8e1f08544afa018a2e61f11","observation_id":"8b629156-3ccb-4c4b-9052-9bb090d9ffe6","resolution":{"observed_at":"2026-08-09T12:32:31.506227Z","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":"2026-08-09T12:32:31.509756Z","title":"A Review of Deep Learning in Medical Imaging: Imaging Traits, Technology Trends, Case Studies with Progress Highlights, and Future Promises","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2502.02624","last_updated":"2025-04-02T08:33:01Z","snapshot_observed_at":"2026-08-09T18:43:30.130567Z","submitted_at":"2025-02-04T14:37:37Z","title":"Muographic Image Upsampling with Machine Learning for Built Infrastructure Applications","version":2},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-09T12:32:31.509756Z"},"links":{"citing_paper":"/paper/2502.02624"},"observation_digest":"sha256:e3f6fc9d6f9eb70813ea60bd0543572726f9643f6fc8126de68fea492899419c","observation_id":"4c3e3c69-03e4-4505-a89a-2ebc70d07450","resolution":{"observed_at":"2026-08-09T12:32:31.509756Z","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":"2026-08-09T12:32:31.512421Z","title":"Segment anything in medical images","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2502.02624","last_updated":"2025-04-02T08:33:01Z","snapshot_observed_at":"2026-08-09T18:43:30.130567Z","submitted_at":"2025-02-04T14:37:37Z","title":"Muographic Image Upsampling with Machine Learning for Built Infrastructure Applications","version":2},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-09T12:32:31.512421Z"},"links":{"citing_paper":"/paper/2502.02624"},"observation_digest":"sha256:c6982c8380ecc3ec2bd15057c0f440b91ec9615ddad60c90c57a9657a7c315ad","observation_id":"d0e12621-86fd-49e3-b132-94ca2ed59eeb","resolution":{"observed_at":"2026-08-09T12:32:31.512421Z","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":"2026-08-09T12:32:31.515312Z","title":"Geant4—A simulation toolkit","venue":null,"work_id":null,"year":2003},"citing_paper":{"arxiv_id":"2502.02624","last_updated":"2025-04-02T08:33:01Z","snapshot_observed_at":"2026-08-09T18:43:30.130567Z","submitted_at":"2025-02-04T14:37:37Z","title":"Muographic Image Upsampling with Machine Learning for Built Infrastructure Applications","version":2},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-09T12:32:31.515312Z"},"links":{"citing_paper":"/paper/2502.02624"},"observation_digest":"sha256:50484025b85ddfde19466f6b7aa739648c630c5bfcb55a3ded61fc28a57dec0d","observation_id":"fb664e30-e108-483e-ab50-2bdd77e8a0ac","resolution":{"observed_at":"2026-08-09T12:32:31.515312Z","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":"2026-08-09T12:32:31.518540Z","title":"Geant4 developments and applications","venue":null,"work_id":null,"year":2006},"citing_paper":{"arxiv_id":"2502.02624","last_updated":"2025-04-02T08:33:01Z","snapshot_observed_at":"2026-08-09T18:43:30.130567Z","submitted_at":"2025-02-04T14:37:37Z","title":"Muographic Image Upsampling with Machine Learning for Built Infrastructure Applications","version":2},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-09T12:32:31.518540Z"},"links":{"citing_paper":"/paper/2502.02624"},"observation_digest":"sha256:f0769f4566929980e0c5cf7625ef6ed790849cb37f57508252d6433c81c50cb9","observation_id":"ac2bd13c-8dbe-41ae-bea5-73579fc50f8a","resolution":{"observed_at":"2026-08-09T12:32:31.518540Z","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":"2026-08-09T12:32:31.521361Z","title":"Recent developments in Geant4","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2502.02624","last_updated":"2025-04-02T08:33:01Z","snapshot_observed_at":"2026-08-09T18:43:30.130567Z","submitted_at":"2025-02-04T14:37:37Z","title":"Muographic Image Upsampling with Machine Learning for Built Infrastructure Applications","version":2},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-09T12:32:31.521361Z"},"links":{"citing_paper":"/paper/2502.02624"},"observation_digest":"sha256:192924aaba24b4f2d02bd6a52d13620a82a2f1e189c17040bab4fba4e19d8f1f","observation_id":"bac393d2-98bd-4fde-9bdb-9de2fcebf845","resolution":{"observed_at":"2026-08-09T12:32:31.521361Z","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":"2021.16573","doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T12:32:32.183711Z","title":"EcoMug: An Efficient COsmic MUon Generator for cosmic-ray muon applications","venue":null,"work_id":"9be2212e-4116-467e-b4cc-be78ce431456","year":2021},"citing_paper":{"arxiv_id":"2502.02624","last_updated":"2025-04-02T08:33:01Z","snapshot_observed_at":"2026-08-09T18:43:30.130567Z","submitted_at":"2025-02-04T14:37:37Z","title":"Muographic Image Upsampling with Machine Learning for Built Infrastructure Applications","version":2},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-09T12:32:31.523972Z"},"links":{"citing_paper":"/paper/2502.02624"},"observation_digest":"sha256:d084894f3e4c30d5241063f919e108e025ddf27165e42cb981cd1eee3e5c4be1","observation_id":"82add171-bb8a-45b9-89fc-d4142c47a925","resolution":{"observed_at":"2026-08-09T12:32:32.189231Z","resolver_source":"raw_fallback","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1103/physrevresearch.2.02","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T12:32:31.695698Z","title":"Muon tomography for railway tunnel imaging","venue":null,"work_id":"9cec578d-f55d-4077-9f4f-d7d21a7d48d1","year":2020},"citing_paper":{"arxiv_id":"2502.02624","last_updated":"2025-04-02T08:33:01Z","snapshot_observed_at":"2026-08-09T18:43:30.130567Z","submitted_at":"2025-02-04T14:37:37Z","title":"Muographic Image Upsampling with Machine Learning for Built Infrastructure Applications","version":2},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-09T12:32:31.526545Z"},"links":{"citing_paper":"/paper/2502.02624"},"observation_digest":"sha256:495769eb172e4801ff3db0320227f1f6f619f5f1ca39dc2417393d71853a1593","observation_id":"3aaeb909-a8c4-4fc9-b49e-7403f099d992","resolution":{"observed_at":"2026-08-09T12:32:31.699074Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-09T12:32:31.529207Z","title":"Structural health monitoring of sabo check dams with cosmic-ray muography","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2502.02624","last_updated":"2025-04-02T08:33:01Z","snapshot_observed_at":"2026-08-09T18:43:30.130567Z","submitted_at":"2025-02-04T14:37:37Z","title":"Muographic Image Upsampling with Machine Learning for Built Infrastructure Applications","version":2},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-09T12:32:31.529207Z"},"links":{"citing_paper":"/paper/2502.02624"},"observation_digest":"sha256:8efb3d871acbaa12c10f929949fbf9becc7252410ac22f2f7c85ac5d69d1230c","observation_id":"6b1e990c-2aed-4711-a71a-3f587c44aff7","resolution":{"observed_at":"2026-08-09T12:32:31.529207Z","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":"2026-08-09T12:32:31.532005Z","title":"Investigation of the Unit-1 nuclear reactor of Fukushima Daiichi by cosmic muon radiography","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2502.02624","last_updated":"2025-04-02T08:33:01Z","snapshot_observed_at":"2026-08-09T18:43:30.130567Z","submitted_at":"2025-02-04T14:37:37Z","title":"Muographic Image Upsampling with Machine Learning for Built Infrastructure Applications","version":2},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-09T12:32:31.532005Z"},"links":{"citing_paper":"/paper/2502.02624"},"observation_digest":"sha256:e0154fd8ea6347f4a37caba8d3a7397ef03dacc975c8f8d24343e6f40b3e4aff","observation_id":"ccf27c7e-113c-47e3-b620-c3db756e239c","resolution":{"observed_at":"2026-08-09T12:32:31.532005Z","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":"10.1038/ncomms4381","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T05:30:23.456663Z","title":"Radiographic visualization of magma dynamics in an erupting volcano","venue":"Nature Communications","work_id":"a6872950-313f-4b64-bb48-c8ee131c0059","year":2014},"citing_paper":{"arxiv_id":"2502.02624","last_updated":"2025-04-02T08:33:01Z","snapshot_observed_at":"2026-08-09T18:43:30.130567Z","submitted_at":"2025-02-04T14:37:37Z","title":"Muographic Image Upsampling with Machine Learning for Built Infrastructure Applications","version":2},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-09T12:32:31.534674Z"},"links":{"citing_paper":"/paper/2502.02624"},"observation_digest":"sha256:70fa04bcd412487750930a6f4678971b1ceea26240aba5d0600e6adb72d88e00","observation_id":"7a4f52d0-ff19-49da-a3d3-f7851ccad52c","resolution":{"observed_at":"2026-08-09T12:32:31.685029Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-09T12:32:31.537626Z","title":"Discovery of a big void in Khufu’s Pyramid by observation of cosmic-ray muons","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2502.02624","last_updated":"2025-04-02T08:33:01Z","snapshot_observed_at":"2026-08-09T18:43:30.130567Z","submitted_at":"2025-02-04T14:37:37Z","title":"Muographic Image Upsampling with Machine Learning for Built Infrastructure Applications","version":2},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-09T12:32:31.537626Z"},"links":{"citing_paper":"/paper/2502.02624"},"observation_digest":"sha256:7ae42c7aa194b2e9a5a41fd8a680c3d7b922882cc64c226353ac84996ac31830","observation_id":"337c53a7-eec8-498f-9b00-d08bad1fa3c9","resolution":{"observed_at":"2026-08-09T12:32:31.537626Z","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":"10.1103/revmodphys.13.240","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T05:30:23.456663Z","title":"Cosmic-Ray Theory","venue":"Reviews of Modern Physics","work_id":"97b14bce-2aea-44b0-98d5-4a66ce7566b0","year":1941},"citing_paper":{"arxiv_id":"2502.02624","last_updated":"2025-04-02T08:33:01Z","snapshot_observed_at":"2026-08-09T18:43:30.130567Z","submitted_at":"2025-02-04T14:37:37Z","title":"Muographic Image Upsampling with Machine Learning for Built Infrastructure Applications","version":2},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-09T12:32:31.540368Z"},"links":{"citing_paper":"/paper/2502.02624"},"observation_digest":"sha256:7451ef11da24b1ff718d036376564e39e674fa6fabce3cfed98d601d8cda0ce0","observation_id":"fb12f32c-7629-4844-81f6-bae144c19937","resolution":{"observed_at":"2026-08-09T12:32:31.670798Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-09T12:32:31.543306Z","title":"Novel muon imaging techniques","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2502.02624","last_updated":"2025-04-02T08:33:01Z","snapshot_observed_at":"2026-08-09T18:43:30.130567Z","submitted_at":"2025-02-04T14:37:37Z","title":"Muographic Image Upsampling with Machine Learning for Built Infrastructure Applications","version":2},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-09T12:32:31.543306Z"},"links":{"citing_paper":"/paper/2502.02624"},"observation_digest":"sha256:6c52a17c9adcb6213b61aa504cfc17c1c700d529f206d2166ed5d9ba085aa563","observation_id":"dd99b50c-dc2e-4a98-97cf-253ea08e478a","resolution":{"observed_at":"2026-08-09T12:32:31.543306Z","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":"10.1063/5.0174796","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T05:30:23.456663Z","title":"Performance evaluation of cosmic ray muon trajectory estimation algorithms","venue":"AIP Advances","work_id":"cdc9bdf9-a9f8-44da-b449-3b7598e0bd63","year":2023},"citing_paper":{"arxiv_id":"2502.02624","last_updated":"2025-04-02T08:33:01Z","snapshot_observed_at":"2026-08-09T18:43:30.130567Z","submitted_at":"2025-02-04T14:37:37Z","title":"Muographic Image Upsampling with Machine Learning for Built Infrastructure Applications","version":2},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-09T12:32:31.545841Z"},"links":{"citing_paper":"/paper/2502.02624"},"observation_digest":"sha256:66346036829e95d2057a7988f43bd82e3d109fdfb88de7d24f52a83ffccf5b74","observation_id":"ec66e1f3-32a3-43b8-8b03-fbe3b6a21138","resolution":{"observed_at":"2026-08-09T12:32:31.661312Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-09T12:32:32.523156Z","title":"Cosmic Ray Muon Radiography","venue":null,"work_id":"067ae209-5260-4ebf-8b4e-d606d64f0907","year":2003},"citing_paper":{"arxiv_id":"2502.02624","last_updated":"2025-04-02T08:33:01Z","snapshot_observed_at":"2026-08-09T18:43:30.130567Z","submitted_at":"2025-02-04T14:37:37Z","title":"Muographic Image Upsampling with Machine Learning for Built Infrastructure Applications","version":2},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-09T12:32:31.549112Z"},"links":{"citing_paper":"/paper/2502.02624"},"observation_digest":"sha256:9d6c8ce4ed778a04aa96598f6da5b7a518e6fc089dc03ae71771eaec760c5d00","observation_id":"ca312675-532b-4bba-9b02-5e1c6624a22f","resolution":{"observed_at":"2026-08-09T12:32:32.526007Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-09T12:32:31.551656Z","title":"& Feldman, G","venue":null,"work_id":null,"year":1968},"citing_paper":{"arxiv_id":"2502.02624","last_updated":"2025-04-02T08:33:01Z","snapshot_observed_at":"2026-08-09T18:43:30.130567Z","submitted_at":"2025-02-04T14:37:37Z","title":"Muographic Image Upsampling with Machine Learning for Built Infrastructure Applications","version":2},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-09T12:32:31.551656Z"},"links":{"citing_paper":"/paper/2502.02624"},"observation_digest":"sha256:4ab2963cedaeec7497441205a11224f26c56f446d53409d6d888458feb9a3246","observation_id":"2e8bbecf-57ad-4bb3-be26-0fffea33d943","resolution":{"observed_at":"2026-08-09T12:32:31.551656Z","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":"2026-08-09T12:32:31.554630Z","title":"U-Net: Convolutional Networks for Biomedical Image Segmentation","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2502.02624","last_updated":"2025-04-02T08:33:01Z","snapshot_observed_at":"2026-08-09T18:43:30.130567Z","submitted_at":"2025-02-04T14:37:37Z","title":"Muographic Image Upsampling with Machine Learning for Built Infrastructure Applications","version":2},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-09T12:32:31.554630Z"},"links":{"citing_paper":"/paper/2502.02624"},"observation_digest":"sha256:3b1b15827d83e78685e16a2b3da1af04a04549b3e4ad0d99de7982f770dbc151","observation_id":"b2b43dca-7fa5-44ff-ba54-c8f2f92fd352","resolution":{"observed_at":"2026-08-09T12:32:31.554630Z","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":"2026-08-09T12:32:31.557400Z","title":"U-Net and Its Variants for Medical Image Segmentation: A Review of Theory and Applications","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2502.02624","last_updated":"2025-04-02T08:33:01Z","snapshot_observed_at":"2026-08-09T18:43:30.130567Z","submitted_at":"2025-02-04T14:37:37Z","title":"Muographic Image Upsampling with Machine Learning for Built Infrastructure Applications","version":2},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-09T12:32:31.557400Z"},"links":{"citing_paper":"/paper/2502.02624"},"observation_digest":"sha256:b60641bc1d2f88575fa2041d8ce3319830e6527cd4d0544639c77cbf1b163c17","observation_id":"96a9f1f8-f79f-4fa5-99f7-27875053407b","resolution":{"observed_at":"2026-08-09T12:32:31.557400Z","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":"2026-08-09T12:32:32.514635Z","title":"Measures of the Amount of Ecologic Association Between Species","venue":null,"work_id":"8c2d9d66-a765-44c7-a628-5dad4c403054","year":1945},"citing_paper":{"arxiv_id":"2502.02624","last_updated":"2025-04-02T08:33:01Z","snapshot_observed_at":"2026-08-09T18:43:30.130567Z","submitted_at":"2025-02-04T14:37:37Z","title":"Muographic Image Upsampling with Machine Learning for Built Infrastructure Applications","version":2},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-09T12:32:31.560640Z"},"links":{"citing_paper":"/paper/2502.02624"},"observation_digest":"sha256:7093e7918361e0523762b03b68960a206a18356019d592770498392cdb68676b","observation_id":"c3e5115a-5c6a-4fe6-b6b1-796f00930d73","resolution":{"observed_at":"2026-08-09T12:32:32.517761Z","resolver_source":"raw_fallback","status":"malformed_identifier"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-09T12:32:32.504753Z","title":"A method of establishing groups of equal amplitude in plant sociology based on similarity of species and its application to analyses of the vegetation on Danish commons","venue":null,"work_id":"557d9070-f894-4f96-a04c-f624796e1cfe","year":1948},"citing_paper":{"arxiv_id":"2502.02624","last_updated":"2025-04-02T08:33:01Z","snapshot_observed_at":"2026-08-09T18:43:30.130567Z","submitted_at":"2025-02-04T14:37:37Z","title":"Muographic Image Upsampling with Machine Learning for Built Infrastructure Applications","version":2},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-09T12:32:31.563845Z"},"links":{"citing_paper":"/paper/2502.02624"},"observation_digest":"sha256:8fba9084241d239ed704f888875481b98192b630c75909a8d051f8e3baf2827c","observation_id":"429df703-a551-4ec8-9ebc-26d2ba41974e","resolution":{"observed_at":"2026-08-09T12:32:32.508232Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-09T12:32:31.566570Z","title":"The design and performance of a scintillating-fibre tracker for the cosmic-ray muon tomography of legacy nuclear waste containers","venue":null,"work_id":null,"year":2014},"citing_paper":{"arxiv_id":"2502.02624","last_updated":"2025-04-02T08:33:01Z","snapshot_observed_at":"2026-08-09T18:43:30.130567Z","submitted_at":"2025-02-04T14:37:37Z","title":"Muographic Image Upsampling with Machine Learning for Built Infrastructure Applications","version":2},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-09T12:32:31.566570Z"},"links":{"citing_paper":"/paper/2502.02624"},"observation_digest":"sha256:11a9ae13e23e7c6a1b496180e0075a5469e8af5344bcfbd33fc51e69679d0c40","observation_id":"68cae875-5372-494b-bf57-3df2a329457d","resolution":{"observed_at":"2026-08-09T12:32:31.566570Z","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":"2026-08-09T12:32:31.569352Z","title":"Air void clustering in concrete and its effect on concrete strength.Int","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2502.02624","last_updated":"2025-04-02T08:33:01Z","snapshot_observed_at":"2026-08-09T18:43:30.130567Z","submitted_at":"2025-02-04T14:37:37Z","title":"Muographic Image Upsampling with Machine Learning for Built Infrastructure Applications","version":2},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-09T12:32:31.569352Z"},"links":{"citing_paper":"/paper/2502.02624"},"observation_digest":"sha256:8c8bb28f8dccce5b276da8e83d73e23f4ba73d6a53d595caa17d379fec4fea27","observation_id":"86b06f43-e0e6-4666-989c-d0deabdcb7ca","resolution":{"observed_at":"2026-08-09T12:32:31.569352Z","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":"2026-08-09T12:32:31.572086Z","title":"Image-to-Image Translation with Conditional Adversarial Networks","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2502.02624","last_updated":"2025-04-02T08:33:01Z","snapshot_observed_at":"2026-08-09T18:43:30.130567Z","submitted_at":"2025-02-04T14:37:37Z","title":"Muographic Image Upsampling with Machine Learning for Built Infrastructure Applications","version":2},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-09T12:32:31.572086Z"},"links":{"citing_paper":"/paper/2502.02624"},"observation_digest":"sha256:b6335c478ea6027156dc60ea895ea188f9a07a27ef99bfa70ff1a458fd16d5fd","observation_id":"dcb7b40c-7cf7-4ea3-88ef-4ad8bd49819e","resolution":{"observed_at":"2026-08-09T12:32:31.572086Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1701.07875","last_updated":"2017-12-06T20:01:54Z","snapshot_observed_at":"2026-07-06T05:27:45.080675Z","submitted_at":"2017-01-26T21:10:29Z","title":"Wasserstein GAN","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1701.07875","snapshot_observed_at":"2026-08-09T12:32:31.575088Z","title":"Wasserstein GAN","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2502.02624","last_updated":"2025-04-02T08:33:01Z","snapshot_observed_at":"2026-08-09T18:43:30.130567Z","submitted_at":"2025-02-04T14:37:37Z","title":"Muographic Image Upsampling with Machine Learning for Built Infrastructure Applications","version":2},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-09T12:32:31.575088Z"},"links":{"cited_paper":"/paper/1701.07875","citing_paper":"/paper/2502.02624"},"observation_digest":"sha256:d93498d7e8c998e7e8ef66fec66628789a602af0692a4ffa1619282d5a9ad416","observation_id":"df8f4171-37fa-4108-90e4-690897648f71","resolution":{"observed_at":"2026-08-09T12:32:31.575088Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1704.00028","last_updated":"2017-12-25T23:03:49Z","snapshot_observed_at":"2026-08-10T12:15:09.941778Z","submitted_at":"2017-03-31T19:25:00Z","title":"Improved Training of Wasserstein GANs","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1704.00028","snapshot_observed_at":"2026-08-09T12:32:31.578597Z","title":"Improved Training of Wasserstein GANs","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2502.02624","last_updated":"2025-04-02T08:33:01Z","snapshot_observed_at":"2026-08-09T18:43:30.130567Z","submitted_at":"2025-02-04T14:37:37Z","title":"Muographic Image Upsampling with Machine Learning for Built Infrastructure Applications","version":2},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-09T12:32:31.578597Z"},"links":{"cited_paper":"/paper/1704.00028","citing_paper":"/paper/2502.02624"},"observation_digest":"sha256:143fab86e00d22f1276a76340beeb115a29f78c27f6dd7483d1d53808da32222","observation_id":"e96f6090-e8e8-4691-81c7-483fbaf7b962","resolution":{"observed_at":"2026-08-09T12:32:31.578597Z","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":"2026-08-09T12:32:31.581879Z","title":"Image Quality Assessment: From Error Visibility to Structural Similarity","venue":null,"work_id":null,"year":2004},"citing_paper":{"arxiv_id":"2502.02624","last_updated":"2025-04-02T08:33:01Z","snapshot_observed_at":"2026-08-09T18:43:30.130567Z","submitted_at":"2025-02-04T14:37:37Z","title":"Muographic Image Upsampling with Machine Learning for Built Infrastructure Applications","version":2},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-09T12:32:31.581879Z"},"links":{"citing_paper":"/paper/2502.02624"},"observation_digest":"sha256:465733a270cc6363e41120319cf0e9b94b273c862feec8203d187bf68cbed1ee","observation_id":"994ba147-3c7d-4abb-874e-7644184ba0f2","resolution":{"observed_at":"2026-08-09T12:32:31.581879Z","resolver_source":null,"status":"malformed_identifier"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1802.02611","last_updated":"2018-08-22T20:41:10Z","snapshot_observed_at":"2026-07-06T06:22:17.424495Z","submitted_at":"2018-02-07T19:37:11Z","title":"Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1802.02611","snapshot_observed_at":"2026-08-09T12:32:31.585048Z","title":"Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2502.02624","last_updated":"2025-04-02T08:33:01Z","snapshot_observed_at":"2026-08-09T18:43:30.130567Z","submitted_at":"2025-02-04T14:37:37Z","title":"Muographic Image Upsampling with Machine Learning for Built Infrastructure Applications","version":2},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-09T12:32:31.585048Z"},"links":{"cited_paper":"/paper/1802.02611","citing_paper":"/paper/2502.02624"},"observation_digest":"sha256:8fa7fb81518c8e2cec4326dbe704c60bdfa381b5bf8ab6b1724f5d752cf8d1d1","observation_id":"0f4eaacd-684e-424e-8aa5-c98f0666b24b","resolution":{"observed_at":"2026-08-09T12:32:31.585048Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1706.03762","last_updated":"2023-08-02T00:41:18Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2017-06-12T17:57:34Z","title":"Attention Is All You Need","version":7},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1706.03762","snapshot_observed_at":"2026-08-09T12:32:31.588566Z","title":"Attention Is All You Need","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2502.02624","last_updated":"2025-04-02T08:33:01Z","snapshot_observed_at":"2026-08-09T18:43:30.130567Z","submitted_at":"2025-02-04T14:37:37Z","title":"Muographic Image Upsampling with Machine Learning for Built Infrastructure Applications","version":2},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-09T12:32:31.588566Z"},"links":{"cited_paper":"/paper/1706.03762","citing_paper":"/paper/2502.02624"},"observation_digest":"sha256:badfdce45d731baf1b94a8829c1613fbd891754739d654f1401f81a29585db04","observation_id":"f7126ac6-42f2-4b69-ab2f-366c14863c12","resolution":{"observed_at":"2026-08-09T12:32:31.588566Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2502.02624","last_updated":"2025-04-02T08:33:01Z","latest_version":2,"primary_category":"eess.IV","snapshot_observed_at":"2026-08-09T18:43:30.130567Z","submitted_at":"2025-02-04T14:37:37Z","title":"Muographic Image Upsampling with Machine Learning for Built Infrastructure Applications"},"reference_resolution":{"displayed":37,"state_counts":{"malformed_identifier":4,"metadata_mismatch":1,"parse_uncertain":0,"unresolved":22,"verified_exact":8,"verified_fuzzy":2},"total_outbound_references":37},"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":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"thesis":"As of 11 August 2026, this Paper Citation Record lists 37 of 37 outbound references and 0 inbound Pith citation observations for arXiv:2502.02624."}