{"as_of":"2026-08-13T14:44:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:7687e6c8c9b90509e506581a7b1f955a3f3a184e16f30061761d5ce2346a8648","coverage":[{"denominator":51,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":51,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-12T13:09:48.186963Z","state":"measured"},{"denominator":51,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":51,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-13T06:32:02.005865+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/2411.16439/citation-record","integrity":"/paper/2411.16439/integrity","json":"/paper/2411.16439/citation-record.json","paper":"/paper/2411.16439"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T13:09:49.123266Z","title":"Quantitative measurement of size and three-dimensional position of fast-moving bubbles in air-water mixture flows using digital holography,","venue":null,"work_id":"f0657b8a-6035-40e9-9e19-e3df96a6f150","year":2010},"citing_paper":{"arxiv_id":"2411.16439","last_updated":"2024-11-25T14:40:04Z","snapshot_observed_at":"2026-08-12T13:04:13.120869Z","submitted_at":"2024-11-25T14:40:04Z","title":"Generalizable Deep Learning Approach for 3D Particle Imaging using Holographic Microscopy","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-12T13:09:47.895239Z"},"links":{"citing_paper":"/paper/2411.16439"},"observation_digest":"sha256:ec393a75654dc54898839444f2d0732bee94024e3e04b4578050265fe9023d4b","observation_id":"fd3905a5-9aee-4e89-9bbc-5d435c762553","resolution":{"observed_at":"2026-08-12T13:09:49.127686Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-12T13:09:49.108484Z","title":"Applications of holography in fluid mechanics and particle dynamics,","venue":null,"work_id":"51d0f77b-8633-4128-bd3d-94e2faa89f76","year":2010},"citing_paper":{"arxiv_id":"2411.16439","last_updated":"2024-11-25T14:40:04Z","snapshot_observed_at":"2026-08-12T13:04:13.120869Z","submitted_at":"2024-11-25T14:40:04Z","title":"Generalizable Deep Learning Approach for 3D Particle Imaging using Holographic Microscopy","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-12T13:09:47.901547Z"},"links":{"citing_paper":"/paper/2411.16439"},"observation_digest":"sha256:d5e427167bceef60563d0062af0d03999dee23064f294d468e2105358269e904","observation_id":"84fd31ca-5449-49af-a16d-8fc9f4091b81","resolution":{"observed_at":"2026-08-12T13:09:49.112850Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-12T13:09:49.094505Z","title":"Tutorial: Aerosol characterization with digital in-line holography,","venue":null,"work_id":"ecad2e65-a900-4a43-9f2a-7db4f0e7aeba","year":2022},"citing_paper":{"arxiv_id":"2411.16439","last_updated":"2024-11-25T14:40:04Z","snapshot_observed_at":"2026-08-12T13:04:13.120869Z","submitted_at":"2024-11-25T14:40:04Z","title":"Generalizable Deep Learning Approach for 3D Particle Imaging using Holographic Microscopy","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-12T13:09:47.907999Z"},"links":{"citing_paper":"/paper/2411.16439"},"observation_digest":"sha256:328ea35d476a94a10583549170445e48a80987a2bb9619de29494b5e5e51e05d","observation_id":"eecaa9f1-9e39-48dd-b46a-89ccb5985e59","resolution":{"observed_at":"2026-08-12T13:09:49.098619Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-12T13:09:49.079854Z","title":"Kim and M.K","venue":null,"work_id":"b3059284-7750-4510-9e92-52eaf8e5870f","year":2011},"citing_paper":{"arxiv_id":"2411.16439","last_updated":"2024-11-25T14:40:04Z","snapshot_observed_at":"2026-08-12T13:04:13.120869Z","submitted_at":"2024-11-25T14:40:04Z","title":"Generalizable Deep Learning Approach for 3D Particle Imaging using Holographic Microscopy","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-12T13:09:47.913732Z"},"links":{"citing_paper":"/paper/2411.16439"},"observation_digest":"sha256:35c23a34c2d98899210ca90ed4d4d865fcd268b009b52172dfd21d80cd6a9452","observation_id":"cbf82d04-05b9-494b-8b14-d34b31dbaf18","resolution":{"observed_at":"2026-08-12T13:09:49.084779Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-12T13:09:49.064868Z","title":"Lensless imaging and sensing,","venue":null,"work_id":"8bba0432-0e9a-47b4-bbb4-758b40acd016","year":2016},"citing_paper":{"arxiv_id":"2411.16439","last_updated":"2024-11-25T14:40:04Z","snapshot_observed_at":"2026-08-12T13:04:13.120869Z","submitted_at":"2024-11-25T14:40:04Z","title":"Generalizable Deep Learning Approach for 3D Particle Imaging using Holographic Microscopy","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-12T13:09:47.919092Z"},"links":{"citing_paper":"/paper/2411.16439"},"observation_digest":"sha256:292ef80f8cda220dc789c156ce9e19ed430991ad5f40d4b6edf402645f85c238","observation_id":"788e32ec-1048-46a9-b10b-bc28bd1f270a","resolution":{"observed_at":"2026-08-12T13:09:49.069472Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-12T13:09:49.049506Z","title":"Holographic characterization of protein aggregates,","venue":null,"work_id":"c593b10b-87f9-425b-8e2c-e1d7143d62f7","year":2016},"citing_paper":{"arxiv_id":"2411.16439","last_updated":"2024-11-25T14:40:04Z","snapshot_observed_at":"2026-08-12T13:04:13.120869Z","submitted_at":"2024-11-25T14:40:04Z","title":"Generalizable Deep Learning Approach for 3D Particle Imaging using Holographic Microscopy","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-12T13:09:47.925166Z"},"links":{"citing_paper":"/paper/2411.16439"},"observation_digest":"sha256:86abaaead94602f895c3ed8156864a988ddbead5a4eac5230e875e0c9ca53da9","observation_id":"81d91e2d-7798-42d8-95e7-962f0625f5e4","resolution":{"observed_at":"2026-08-12T13:09:49.054120Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-12T13:09:49.035747Z","title":"Non -destructive inspection and quantification of soldering defects in PCB using an autofocusing digital holographic camera,","venue":null,"work_id":"54d1d519-f3b3-46c3-b344-42c5c0049bc5","year":2023},"citing_paper":{"arxiv_id":"2411.16439","last_updated":"2024-11-25T14:40:04Z","snapshot_observed_at":"2026-08-12T13:04:13.120869Z","submitted_at":"2024-11-25T14:40:04Z","title":"Generalizable Deep Learning Approach for 3D Particle Imaging using Holographic Microscopy","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-12T13:09:47.933084Z"},"links":{"citing_paper":"/paper/2411.16439"},"observation_digest":"sha256:115fbba9f68a95b63dfb6714b2e2545b1f87abeb337010ed7232b0fff00393ba","observation_id":"c9f34d5d-6a61-442d-9843-fdf5445fbc38","resolution":{"observed_at":"2026-08-12T13:09:49.040245Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-12T13:09:49.021889Z","title":"Design of an in-line, digital holographic imaging system for airborne measurement of clouds,","venue":null,"work_id":"8c579c0b-ff67-4b2a-85df-4fc69301659e","year":2011},"citing_paper":{"arxiv_id":"2411.16439","last_updated":"2024-11-25T14:40:04Z","snapshot_observed_at":"2026-08-12T13:04:13.120869Z","submitted_at":"2024-11-25T14:40:04Z","title":"Generalizable Deep Learning Approach for 3D Particle Imaging using Holographic Microscopy","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-12T13:09:47.938304Z"},"links":{"citing_paper":"/paper/2411.16439"},"observation_digest":"sha256:ac14931079e9b9e1d5ac0070752cfcd28b5de678dfd7d489502ed77fdef9b1fc","observation_id":"82fd89af-f027-40b6-a577-15ec43780fac","resolution":{"observed_at":"2026-08-12T13:09:49.026480Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-12T13:09:49.007600Z","title":"Imaging atmospheric aerosol particles from a UAV with digital holography,","venue":null,"work_id":"2727c799-3b26-439c-a274-a2ececdc50ee","year":2020},"citing_paper":{"arxiv_id":"2411.16439","last_updated":"2024-11-25T14:40:04Z","snapshot_observed_at":"2026-08-12T13:04:13.120869Z","submitted_at":"2024-11-25T14:40:04Z","title":"Generalizable Deep Learning Approach for 3D Particle Imaging using Holographic Microscopy","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-12T13:09:47.944013Z"},"links":{"citing_paper":"/paper/2411.16439"},"observation_digest":"sha256:6b5e59f4b8dc8d7d00bcdbc62102d71a07d7de914c87e84852dc246eddcfebef","observation_id":"66214a17-c1b1-4670-85fb-1acf694763f1","resolution":{"observed_at":"2026-08-12T13:09:49.012029Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-12T13:09:48.993226Z","title":"Visualization and characterization of agricultural sprays using machine learning based digital inline holography,","venue":null,"work_id":"5d361684-94d5-4977-aa37-5631681cc71d","year":2024},"citing_paper":{"arxiv_id":"2411.16439","last_updated":"2024-11-25T14:40:04Z","snapshot_observed_at":"2026-08-12T13:04:13.120869Z","submitted_at":"2024-11-25T14:40:04Z","title":"Generalizable Deep Learning Approach for 3D Particle Imaging using Holographic Microscopy","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-12T13:09:47.949610Z"},"links":{"citing_paper":"/paper/2411.16439"},"observation_digest":"sha256:f602ba0227f46714a089aa54304a330cc1b770c577692a782ddbac052534e1e4","observation_id":"4f7081aa-7d5e-41ca-a932-c7d4a9815625","resolution":{"observed_at":"2026-08-12T13:09:48.997873Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-12T13:09:48.978420Z","title":"Three-dimensional volumetric monitoring of settling particulate matters on a leaf using digital in-line holographic microscopy,","venue":null,"work_id":"d997f6ab-f687-4a32-9789-1d70ddcd5a84","year":2021},"citing_paper":{"arxiv_id":"2411.16439","last_updated":"2024-11-25T14:40:04Z","snapshot_observed_at":"2026-08-12T13:04:13.120869Z","submitted_at":"2024-11-25T14:40:04Z","title":"Generalizable Deep Learning Approach for 3D Particle Imaging using Holographic Microscopy","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-12T13:09:47.955300Z"},"links":{"citing_paper":"/paper/2411.16439"},"observation_digest":"sha256:a81b6b31f113ab084e647a8c501c4b2cd95d9f9b987e227ba73a912b0e01a5c5","observation_id":"af8c095b-dcfb-43e8-9fbe-85e357d65af9","resolution":{"observed_at":"2026-08-12T13:09:48.983066Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-12T13:09:48.963021Z","title":"Digital in-line holography with photons and electrons,","venue":null,"work_id":"61c715c5-f34f-4e6e-85dc-b9489a0777d5","year":2001},"citing_paper":{"arxiv_id":"2411.16439","last_updated":"2024-11-25T14:40:04Z","snapshot_observed_at":"2026-08-12T13:04:13.120869Z","submitted_at":"2024-11-25T14:40:04Z","title":"Generalizable Deep Learning Approach for 3D Particle Imaging using Holographic Microscopy","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-12T13:09:47.960809Z"},"links":{"citing_paper":"/paper/2411.16439"},"observation_digest":"sha256:be92c98678f9c4c80d9a4248f6b588837f9f2d5ba3db57a9fdb326ef966f5202","observation_id":"822fecd3-1758-4e56-b8da-6ab462c4b98d","resolution":{"observed_at":"2026-08-12T13:09:48.967987Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-12T13:09:48.947794Z","title":"Optical conveyors: a class of active tractor beams,","venue":null,"work_id":"977ff99b-5e68-4cc0-a36e-f232372ff0aa","year":2012},"citing_paper":{"arxiv_id":"2411.16439","last_updated":"2024-11-25T14:40:04Z","snapshot_observed_at":"2026-08-12T13:04:13.120869Z","submitted_at":"2024-11-25T14:40:04Z","title":"Generalizable Deep Learning Approach for 3D Particle Imaging using Holographic Microscopy","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-12T13:09:47.966184Z"},"links":{"citing_paper":"/paper/2411.16439"},"observation_digest":"sha256:3dafac255622d9df583d2c109120084f2f05274257c4319bfcd6d81252ebcab1","observation_id":"08656476-037e-4086-a222-723de1847eee","resolution":{"observed_at":"2026-08-12T13:09:48.952633Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-12T13:09:48.933635Z","title":"Digital holographic microscopy reveals prey-induced changes in swimming behavior of predatory dinoflagellates,","venue":null,"work_id":"80e9a2e9-17fa-4e94-8c37-7834101faca4","year":2007},"citing_paper":{"arxiv_id":"2411.16439","last_updated":"2024-11-25T14:40:04Z","snapshot_observed_at":"2026-08-12T13:04:13.120869Z","submitted_at":"2024-11-25T14:40:04Z","title":"Generalizable Deep Learning Approach for 3D Particle Imaging using Holographic Microscopy","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-12T13:09:47.971867Z"},"links":{"citing_paper":"/paper/2411.16439"},"observation_digest":"sha256:0483b16e7395eb49e83db598ce258701a9972066e79649d45b9fda1b7d759a89","observation_id":"71b677bd-a0b4-4837-8041-1d53a5c69ccb","resolution":{"observed_at":"2026-08-12T13:09:48.938264Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-12T13:09:48.919256Z","title":"Review of digital holographic microscopy for three - dimensional profiling and tracking,","venue":null,"work_id":"a8e80898-4525-440d-8af6-9c04fbb1ec6c","year":2014},"citing_paper":{"arxiv_id":"2411.16439","last_updated":"2024-11-25T14:40:04Z","snapshot_observed_at":"2026-08-12T13:04:13.120869Z","submitted_at":"2024-11-25T14:40:04Z","title":"Generalizable Deep Learning Approach for 3D Particle Imaging using Holographic Microscopy","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-12T13:09:47.977511Z"},"links":{"citing_paper":"/paper/2411.16439"},"observation_digest":"sha256:7d025196b40e73ee1f2f9018e080217249b79e3fa1c29723830a091f439904c7","observation_id":"33773c65-9865-45b8-883f-422fcfab6f2d","resolution":{"observed_at":"2026-08-12T13:09:48.923599Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-12T13:09:48.904494Z","title":"Recent advances in holographic 3D particle tracking,","venue":null,"work_id":"1e263ea0-f4d9-4588-b305-63b5f2ee1bf6","year":2015},"citing_paper":{"arxiv_id":"2411.16439","last_updated":"2024-11-25T14:40:04Z","snapshot_observed_at":"2026-08-12T13:04:13.120869Z","submitted_at":"2024-11-25T14:40:04Z","title":"Generalizable Deep Learning Approach for 3D Particle Imaging using Holographic Microscopy","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-12T13:09:47.983092Z"},"links":{"citing_paper":"/paper/2411.16439"},"observation_digest":"sha256:e787745643a6573fd8d28c9c2270f7f5e877ac815fdec512f094a4259e7f2004","observation_id":"0f29592d-7263-46d5-ae11-c8eb21e68c8d","resolution":{"observed_at":"2026-08-12T13:09:48.909171Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-12T13:09:48.891154Z","title":"High fidelity digital inline holographic method for 3D flow measurements,","venue":null,"work_id":"75a963de-7d8b-4735-af40-b5947607118a","year":2015},"citing_paper":{"arxiv_id":"2411.16439","last_updated":"2024-11-25T14:40:04Z","snapshot_observed_at":"2026-08-12T13:04:13.120869Z","submitted_at":"2024-11-25T14:40:04Z","title":"Generalizable Deep Learning Approach for 3D Particle Imaging using Holographic Microscopy","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-12T13:09:47.988299Z"},"links":{"citing_paper":"/paper/2411.16439"},"observation_digest":"sha256:ae5d464d039abe29d93e0b0a8dfe7a7956b3da602abc1e12b1446fcae6ea4d65","observation_id":"af97effc-34ba-4f7e-a190-369c90a92c8b","resolution":{"observed_at":"2026-08-12T13:09:48.895472Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-12T13:09:48.877085Z","title":"Digital in -line holography: influence of the shadow density on particle field extraction,","venue":null,"work_id":"4ef344da-0bbb-4004-9a00-5cac7a65136f","year":2004},"citing_paper":{"arxiv_id":"2411.16439","last_updated":"2024-11-25T14:40:04Z","snapshot_observed_at":"2026-08-12T13:04:13.120869Z","submitted_at":"2024-11-25T14:40:04Z","title":"Generalizable Deep Learning Approach for 3D Particle Imaging using Holographic Microscopy","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-12T13:09:47.993272Z"},"links":{"citing_paper":"/paper/2411.16439"},"observation_digest":"sha256:0da5f68afa829639abecd336d40f98a2637a7411a238c936422af91b5a37df76","observation_id":"48e6a64a-52cb-4931-bd28-f8ed3c26ea4d","resolution":{"observed_at":"2026-08-12T13:09:48.881418Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-12T13:09:48.862270Z","title":"Refinement of particle detection by the hybrid method in digital in-line holography,","venue":null,"work_id":"4df0955b-2555-462c-b26b-6e6252f9aceb","year":2014},"citing_paper":{"arxiv_id":"2411.16439","last_updated":"2024-11-25T14:40:04Z","snapshot_observed_at":"2026-08-12T13:04:13.120869Z","submitted_at":"2024-11-25T14:40:04Z","title":"Generalizable Deep Learning Approach for 3D Particle Imaging using Holographic Microscopy","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-12T13:09:47.998383Z"},"links":{"citing_paper":"/paper/2411.16439"},"observation_digest":"sha256:70180d15d36557007bc7550eee65c7f1398e7e0f3e530d80ed6703387b81ccc5","observation_id":"c28aa0a0-cdb5-4bce-8ac5-a91846478009","resolution":{"observed_at":"2026-08-12T13:09:48.867045Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-12T13:09:48.848370Z","title":"Accurate size measurement of needle -shaped particles using digital holography,","venue":null,"work_id":"298b7476-f905-4c93-b286-485104b37636","year":2011},"citing_paper":{"arxiv_id":"2411.16439","last_updated":"2024-11-25T14:40:04Z","snapshot_observed_at":"2026-08-12T13:04:13.120869Z","submitted_at":"2024-11-25T14:40:04Z","title":"Generalizable Deep Learning Approach for 3D Particle Imaging using Holographic Microscopy","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-12T13:09:48.004309Z"},"links":{"citing_paper":"/paper/2411.16439"},"observation_digest":"sha256:baf226520815e3c3fa9ece1271332d9aa4c4ed9485dbe008b324ea9a34cde770","observation_id":"895031f5-f542-4772-8030-3dedfa1e9b47","resolution":{"observed_at":"2026-08-12T13:09:48.852738Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-12T13:09:48.833986Z","title":"Deep learning in holography and coherent imaging,","venue":null,"work_id":"eccc6163-a54f-4bd3-ac53-19e2db9ff57f","year":2019},"citing_paper":{"arxiv_id":"2411.16439","last_updated":"2024-11-25T14:40:04Z","snapshot_observed_at":"2026-08-12T13:04:13.120869Z","submitted_at":"2024-11-25T14:40:04Z","title":"Generalizable Deep Learning Approach for 3D Particle Imaging using Holographic Microscopy","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-12T13:09:48.010155Z"},"links":{"citing_paper":"/paper/2411.16439"},"observation_digest":"sha256:f13db9f6aafb0910decff8ac613cd89ada7b23dec6197f3d582b6551dc00d5ff","observation_id":"ba9afc49-d73a-41e7-9f61-49ed568b179c","resolution":{"observed_at":"2026-08-12T13:09:48.838257Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-12T13:09:48.819404Z","title":"Roadmap on digital holography,","venue":null,"work_id":"40e965d4-478d-41e9-bf26-03aa501f77d3","year":2021},"citing_paper":{"arxiv_id":"2411.16439","last_updated":"2024-11-25T14:40:04Z","snapshot_observed_at":"2026-08-12T13:04:13.120869Z","submitted_at":"2024-11-25T14:40:04Z","title":"Generalizable Deep Learning Approach for 3D Particle Imaging using Holographic Microscopy","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-12T13:09:48.015590Z"},"links":{"citing_paper":"/paper/2411.16439"},"observation_digest":"sha256:9a8aa01d544c9374fe4ce808d6a32a73ff7aed5da9835d10afd7a983dbb69039","observation_id":"58e416a3-9b4f-4b16-b73b-c2104c43e9a7","resolution":{"observed_at":"2026-08-12T13:09:48.823825Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-12T13:09:48.804369Z","title":"Deep learning for digital holography: a review,","venue":null,"work_id":"42d1eb55-3f9f-4239-87ff-33dd973a000a","year":2021},"citing_paper":{"arxiv_id":"2411.16439","last_updated":"2024-11-25T14:40:04Z","snapshot_observed_at":"2026-08-12T13:04:13.120869Z","submitted_at":"2024-11-25T14:40:04Z","title":"Generalizable Deep Learning Approach for 3D Particle Imaging using Holographic Microscopy","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-12T13:09:48.021209Z"},"links":{"citing_paper":"/paper/2411.16439"},"observation_digest":"sha256:c7e26f8d8711a5230b644429af7f401686f9291199163a01bbf30a3893d3cc35","observation_id":"db5f9d09-0bc5-4e2f-aafb-4f84c201f98b","resolution":{"observed_at":"2026-08-12T13:09:48.809494Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-12T13:09:48.790595Z","title":"Recent advances and applications of digital holography in multiphase reactive/nonreactive flows: a review,","venue":null,"work_id":"243a682d-1f8f-4dee-8fdd-66e7bca7c4fa","year":2021},"citing_paper":{"arxiv_id":"2411.16439","last_updated":"2024-11-25T14:40:04Z","snapshot_observed_at":"2026-08-12T13:04:13.120869Z","submitted_at":"2024-11-25T14:40:04Z","title":"Generalizable Deep Learning Approach for 3D Particle Imaging using Holographic Microscopy","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-12T13:09:48.027231Z"},"links":{"citing_paper":"/paper/2411.16439"},"observation_digest":"sha256:e266742fddce0b65ed12beda4317e61bda4e90f5227d8dad7bd45cf6119cdd06","observation_id":"5a3502dd-a301-4ce0-b149-139b68292ad8","resolution":{"observed_at":"2026-08-12T13:09:48.795277Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-12T13:09:48.777209Z","title":"Machine learning enables precise holographic characterization of colloidal materials in real time,","venue":null,"work_id":"51227db5-eda3-448e-98fd-03e44964cb96","year":2023},"citing_paper":{"arxiv_id":"2411.16439","last_updated":"2024-11-25T14:40:04Z","snapshot_observed_at":"2026-08-12T13:04:13.120869Z","submitted_at":"2024-11-25T14:40:04Z","title":"Generalizable Deep Learning Approach for 3D Particle Imaging using Holographic Microscopy","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-12T13:09:48.032690Z"},"links":{"citing_paper":"/paper/2411.16439"},"observation_digest":"sha256:8ea7ef3d0e54a4c27e9003862c0cc7676b744849c7bc53fc446756aa440e0542","observation_id":"323e0014-8d30-4140-920c-fa47b4c5bbad","resolution":{"observed_at":"2026-08-12T13:09:48.781377Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-12T13:09:48.763929Z","title":"Particle generation and dispersion from high-speed dental drilling,","venue":null,"work_id":"4fbc2455-fa40-4932-be32-59c94cc82d0b","year":2023},"citing_paper":{"arxiv_id":"2411.16439","last_updated":"2024-11-25T14:40:04Z","snapshot_observed_at":"2026-08-12T13:04:13.120869Z","submitted_at":"2024-11-25T14:40:04Z","title":"Generalizable Deep Learning Approach for 3D Particle Imaging using Holographic Microscopy","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-12T13:09:48.038377Z"},"links":{"citing_paper":"/paper/2411.16439"},"observation_digest":"sha256:9d5913a2f4c9bdea7a16dd8f03c1f32cbab1d20552d55479c5851754b3948d29","observation_id":"75d9002c-150a-4626-a49f-06015798c243","resolution":{"observed_at":"2026-08-12T13:09:48.768139Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-12T13:09:48.749046Z","title":"Adaptive in-focus particle detection and segmentation in holographic 3D image with mechanism - guided machine learning,","venue":null,"work_id":"6a80d7db-03ee-43c8-8a2d-14c88dbe2cce","year":2024},"citing_paper":{"arxiv_id":"2411.16439","last_updated":"2024-11-25T14:40:04Z","snapshot_observed_at":"2026-08-12T13:04:13.120869Z","submitted_at":"2024-11-25T14:40:04Z","title":"Generalizable Deep Learning Approach for 3D Particle Imaging using Holographic Microscopy","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-12T13:09:48.045260Z"},"links":{"citing_paper":"/paper/2411.16439"},"observation_digest":"sha256:fd110fbe5016f0aa3f2e216375ef619d599fa7d39ba24c88e2953967a9dab9ea","observation_id":"cd2ceb52-4a05-42d6-9d83-3787aff6600d","resolution":{"observed_at":"2026-08-12T13:09:48.753830Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-12T13:09:48.734987Z","title":"Real-time 3D tracking of swimming microbes using digital holographic microscopy and deep learning,","venue":null,"work_id":"86943488-6825-4fb2-bc62-52c9d570772d","year":2024},"citing_paper":{"arxiv_id":"2411.16439","last_updated":"2024-11-25T14:40:04Z","snapshot_observed_at":"2026-08-12T13:04:13.120869Z","submitted_at":"2024-11-25T14:40:04Z","title":"Generalizable Deep Learning Approach for 3D Particle Imaging using Holographic Microscopy","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-12T13:09:48.063691Z"},"links":{"citing_paper":"/paper/2411.16439"},"observation_digest":"sha256:3c3fbff58e79cb9ed984da502bcb568d5b2e867634108cc72314e5784869f044","observation_id":"57f04ad1-2bca-49c6-9c7f-d42ecb8a5c33","resolution":{"observed_at":"2026-08-12T13:09:48.739812Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-12T13:09:48.593869Z","title":"Microplastic identification via holographic imaging and machine learning ,","venue":null,"work_id":"b753937c-4f07-44f8-a2f4-71310ccfd483","year":2020},"citing_paper":{"arxiv_id":"2411.16439","last_updated":"2024-11-25T14:40:04Z","snapshot_observed_at":"2026-08-12T13:04:13.120869Z","submitted_at":"2024-11-25T14:40:04Z","title":"Generalizable Deep Learning Approach for 3D Particle Imaging using Holographic Microscopy","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-12T13:09:48.070168Z"},"links":{"citing_paper":"/paper/2411.16439"},"observation_digest":"sha256:422cad76278e2a28fdbaf1cb5534e33bfc0e88b7906e0010d605bbc91a68f266","observation_id":"4b0429a7-ec70-49fc-a2f7-f1e2e92a2902","resolution":{"observed_at":"2026-08-12T13:09:48.724732Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-12T13:09:48.576265Z","title":"No-search focus prediction at the single cell level in digital holographic imaging with deep convolutional neural network,","venue":null,"work_id":"68d32d1e-1d0e-4e4b-b692-e9bbaeb494ca","year":2019},"citing_paper":{"arxiv_id":"2411.16439","last_updated":"2024-11-25T14:40:04Z","snapshot_observed_at":"2026-08-12T13:04:13.120869Z","submitted_at":"2024-11-25T14:40:04Z","title":"Generalizable Deep Learning Approach for 3D Particle Imaging using Holographic Microscopy","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-12T13:09:48.075389Z"},"links":{"citing_paper":"/paper/2411.16439"},"observation_digest":"sha256:be6c12999e939f8c563b9944a6b540ee64695cad196ec29bd0c8d67044531cfc","observation_id":"9d4659e2-e05d-4273-aaf4-2daf18c7f1f0","resolution":{"observed_at":"2026-08-12T13:09:48.582634Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-12T13:09:48.559690Z","title":"Focus prediction in digital holographic microscopy using deep convolutional neural networks,","venue":null,"work_id":"e4b47e73-2e50-4554-b78a-eeb8088d0018","year":2019},"citing_paper":{"arxiv_id":"2411.16439","last_updated":"2024-11-25T14:40:04Z","snapshot_observed_at":"2026-08-12T13:04:13.120869Z","submitted_at":"2024-11-25T14:40:04Z","title":"Generalizable Deep Learning Approach for 3D Particle Imaging using Holographic Microscopy","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-12T13:09:48.080229Z"},"links":{"citing_paper":"/paper/2411.16439"},"observation_digest":"sha256:d8708f521a45bc7314bbbff6baf962f95b692138e742f9c31e624ac5ad547716","observation_id":"3b342e55-eac8-45d7-8efd-dbeb93cda0a6","resolution":{"observed_at":"2026-08-12T13:09:48.565653Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-12T13:09:48.541864Z","title":"Deep learning-based accurate and rapid tracking of 3D positional information of microparticles using digital holographic microscopy,","venue":null,"work_id":"7eca2825-abc7-4338-b1f4-886153b7a9d3","year":2019},"citing_paper":{"arxiv_id":"2411.16439","last_updated":"2024-11-25T14:40:04Z","snapshot_observed_at":"2026-08-12T13:04:13.120869Z","submitted_at":"2024-11-25T14:40:04Z","title":"Generalizable Deep Learning Approach for 3D Particle Imaging using Holographic Microscopy","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-12T13:09:48.085809Z"},"links":{"citing_paper":"/paper/2411.16439"},"observation_digest":"sha256:0d01615d3c3d0ffad8f70f44768dfe5aaea90782bd990f6d6221e38fac4abb9c","observation_id":"ad4499a8-cf12-4c69-accf-88c6159a60a9","resolution":{"observed_at":"2026-08-12T13:09:48.547540Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-12T13:09:48.524482Z","title":"Deep learning enables high-throughput analysis of particle -aggregation-based biosensors imaged using holography,","venue":null,"work_id":"62298589-82bf-42e1-b646-c99348c51f5d","year":2018},"citing_paper":{"arxiv_id":"2411.16439","last_updated":"2024-11-25T14:40:04Z","snapshot_observed_at":"2026-08-12T13:04:13.120869Z","submitted_at":"2024-11-25T14:40:04Z","title":"Generalizable Deep Learning Approach for 3D Particle Imaging using Holographic Microscopy","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-12T13:09:48.091174Z"},"links":{"citing_paper":"/paper/2411.16439"},"observation_digest":"sha256:31c59f617801e52b10009610ec0098602a3bc6ab07a64dff6ae1bf052cd8e0ee","observation_id":"d76399e2-ddf9-4026-b2c3-99ea2827b3c5","resolution":{"observed_at":"2026-08-12T13:09:48.530114Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-12T13:09:48.508371Z","title":"Holographic image reconstruction with phase recovery and autofocusing using recurrent neural networks,","venue":null,"work_id":"639d4340-74c9-4c51-8026-422aa3b3e876","year":2021},"citing_paper":{"arxiv_id":"2411.16439","last_updated":"2024-11-25T14:40:04Z","snapshot_observed_at":"2026-08-12T13:04:13.120869Z","submitted_at":"2024-11-25T14:40:04Z","title":"Generalizable Deep Learning Approach for 3D Particle Imaging using Holographic Microscopy","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-12T13:09:48.096491Z"},"links":{"citing_paper":"/paper/2411.16439"},"observation_digest":"sha256:633f3cbc5677543c68db7794af40c8cee7432416ef30a2489921a8a8444c0c21","observation_id":"be57452f-22e8-424c-b379-2fb0c9b56f40","resolution":{"observed_at":"2026-08-12T13:09:48.513638Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-12T13:09:48.491220Z","title":"Learning-based nonparametric autofocusing for digital holography,","venue":null,"work_id":"6931e676-dcd0-4fcb-a566-45142fc0e1ca","year":2018},"citing_paper":{"arxiv_id":"2411.16439","last_updated":"2024-11-25T14:40:04Z","snapshot_observed_at":"2026-08-12T13:04:13.120869Z","submitted_at":"2024-11-25T14:40:04Z","title":"Generalizable Deep Learning Approach for 3D Particle Imaging using Holographic Microscopy","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-12T13:09:48.101853Z"},"links":{"citing_paper":"/paper/2411.16439"},"observation_digest":"sha256:b85f2b5676aefe50e0163469c955c0da6e648498a9f2139331982345e23ea0c0","observation_id":"e59f0867-a0f6-419a-aaa6-1808eb9bb0b5","resolution":{"observed_at":"2026-08-12T13:09:48.496781Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-12T13:09:48.475018Z","title":"Holographic 3D particle reconstruction using a one -stage network,","venue":null,"work_id":"d4f05dc0-aa8e-4620-864a-851a57b4109c","year":2022},"citing_paper":{"arxiv_id":"2411.16439","last_updated":"2024-11-25T14:40:04Z","snapshot_observed_at":"2026-08-12T13:04:13.120869Z","submitted_at":"2024-11-25T14:40:04Z","title":"Generalizable Deep Learning Approach for 3D Particle Imaging using Holographic Microscopy","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-12T13:09:48.107560Z"},"links":{"citing_paper":"/paper/2411.16439"},"observation_digest":"sha256:16734a531a9e6293737e7891d3b0b2e269e936b4608e62ee1761da027c3f5148","observation_id":"58cf58c5-986f-45b0-bbbb-c466371e2c6d","resolution":{"observed_at":"2026-08-12T13:09:48.480787Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-12T13:09:48.459390Z","title":"Digital holographic particle volume reconstruction using a deep neural network,","venue":null,"work_id":"dcaafb30-f82e-42dc-9169-7fb4f3b7ef4a","year":2019},"citing_paper":{"arxiv_id":"2411.16439","last_updated":"2024-11-25T14:40:04Z","snapshot_observed_at":"2026-08-12T13:04:13.120869Z","submitted_at":"2024-11-25T14:40:04Z","title":"Generalizable Deep Learning Approach for 3D Particle Imaging using Holographic Microscopy","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-12T13:09:48.112513Z"},"links":{"citing_paper":"/paper/2411.16439"},"observation_digest":"sha256:42c7c16ffa2c1ff69cb199c73497a3a6149fbc676d9add511eef3236dadd9d9d","observation_id":"f8f61342-4359-45c1-a40e-187d1f2e1235","resolution":{"observed_at":"2026-08-12T13:09:48.464741Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-12T13:09:48.442635Z","title":"Machine learning holography for measuring 3D particle distribution,","venue":null,"work_id":"0b3d8eb2-72b5-44b2-8028-9bdd2d4b583a","year":2020},"citing_paper":{"arxiv_id":"2411.16439","last_updated":"2024-11-25T14:40:04Z","snapshot_observed_at":"2026-08-12T13:04:13.120869Z","submitted_at":"2024-11-25T14:40:04Z","title":"Generalizable Deep Learning Approach for 3D Particle Imaging using Holographic Microscopy","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-12T13:09:48.118398Z"},"links":{"citing_paper":"/paper/2411.16439"},"observation_digest":"sha256:7a5ac3dbdb3dbae31fbf5e55ff56dcdf6d388bd7e224a170d91000b203832586","observation_id":"20cdf8ca-e937-414a-8c4e-a0ba536b4ba9","resolution":{"observed_at":"2026-08-12T13:09:48.448576Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-12T13:09:48.426357Z","title":"Machine learning holography for 3D particle field imaging,","venue":null,"work_id":"ffc31914-2e2b-4961-9b0e-fc8af1da6b67","year":2020},"citing_paper":{"arxiv_id":"2411.16439","last_updated":"2024-11-25T14:40:04Z","snapshot_observed_at":"2026-08-12T13:04:13.120869Z","submitted_at":"2024-11-25T14:40:04Z","title":"Generalizable Deep Learning Approach for 3D Particle Imaging using Holographic Microscopy","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-12T13:09:48.123702Z"},"links":{"citing_paper":"/paper/2411.16439"},"observation_digest":"sha256:4260f202201b0a99dbe1eac325582f614fc459d38a61df6ddc5323e95b64e32e","observation_id":"7cd0444d-2a15-47a9-9ebb-a2be4e9a8681","resolution":{"observed_at":"2026-08-12T13:09:48.432143Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-12T13:09:48.408990Z","title":"Holographic 3D particle imaging with model -based deep network,","venue":null,"work_id":"92ce7c3b-d738-41c4-ac3a-41ef51e51395","year":2021},"citing_paper":{"arxiv_id":"2411.16439","last_updated":"2024-11-25T14:40:04Z","snapshot_observed_at":"2026-08-12T13:04:13.120869Z","submitted_at":"2024-11-25T14:40:04Z","title":"Generalizable Deep Learning Approach for 3D Particle Imaging using Holographic Microscopy","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-12T13:09:48.128942Z"},"links":{"citing_paper":"/paper/2411.16439"},"observation_digest":"sha256:3f59da589ec54a5a9a602aaea1606e507c1237069bf692bc6b82ab49a9a7b3b7","observation_id":"0ad02dd5-a1ec-43eb-a6a4-60cb8bd7d028","resolution":{"observed_at":"2026-08-12T13:09:48.415100Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-12T13:09:48.391190Z","title":"Digital in -line holography for biological applications,","venue":null,"work_id":"8a40f5bb-b6a0-446c-84ef-ce181ee85f56","year":2001},"citing_paper":{"arxiv_id":"2411.16439","last_updated":"2024-11-25T14:40:04Z","snapshot_observed_at":"2026-08-12T13:04:13.120869Z","submitted_at":"2024-11-25T14:40:04Z","title":"Generalizable Deep Learning Approach for 3D Particle Imaging using Holographic Microscopy","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-12T13:09:48.134386Z"},"links":{"citing_paper":"/paper/2411.16439"},"observation_digest":"sha256:8b2c31c7d7d0baf274909cca05d980a8e105b861cabe2163abc99e27816ae66c","observation_id":"a731758d-0359-4391-b381-24428d9df4ca","resolution":{"observed_at":"2026-08-12T13:09:48.397267Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-12T13:09:48.374173Z","title":"Recent advances in digital holography,","venue":null,"work_id":"2d2c7c28-67d6-4da3-a33b-e9d99191c8e1","year":2014},"citing_paper":{"arxiv_id":"2411.16439","last_updated":"2024-11-25T14:40:04Z","snapshot_observed_at":"2026-08-12T13:04:13.120869Z","submitted_at":"2024-11-25T14:40:04Z","title":"Generalizable Deep Learning Approach for 3D Particle Imaging using Holographic Microscopy","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-12T13:09:48.139824Z"},"links":{"citing_paper":"/paper/2411.16439"},"observation_digest":"sha256:a7d02bbe3cbbf6ccbbbe85244d6c3bda32859cb92bba37e394e2bac7aaeb490f","observation_id":"920e602b-e306-488f-84e8-9986ed8c683a","resolution":{"observed_at":"2026-08-12T13:09:48.380624Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-12T13:09:48.357780Z","title":"Trends in process analytical technology,","venue":null,"work_id":"b664d642-2afd-49c8-b727-2340d868a63d","year":2010},"citing_paper":{"arxiv_id":"2411.16439","last_updated":"2024-11-25T14:40:04Z","snapshot_observed_at":"2026-08-12T13:04:13.120869Z","submitted_at":"2024-11-25T14:40:04Z","title":"Generalizable Deep Learning Approach for 3D Particle Imaging using Holographic Microscopy","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-12T13:09:48.144969Z"},"links":{"citing_paper":"/paper/2411.16439"},"observation_digest":"sha256:40b31d6af8476b1d1a6edaa40b280886d48fdf63c3f268325f14923ef6fec266","observation_id":"7b7cd274-3556-48e9-b750-040871e719ec","resolution":{"observed_at":"2026-08-12T13:09:48.363655Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-12T13:09:48.340023Z","title":"Atmospheric aerosol diagnostics with UAV -based holographic imaging and computer vision,","venue":null,"work_id":"bee57b70-2bff-416c-a353-cbd611ba6b00","year":2023},"citing_paper":{"arxiv_id":"2411.16439","last_updated":"2024-11-25T14:40:04Z","snapshot_observed_at":"2026-08-12T13:04:13.120869Z","submitted_at":"2024-11-25T14:40:04Z","title":"Generalizable Deep Learning Approach for 3D Particle Imaging using Holographic Microscopy","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-12T13:09:48.150215Z"},"links":{"citing_paper":"/paper/2411.16439"},"observation_digest":"sha256:235a8854b2243c65528028b60362f4b3b8cdfd51d407d6b0b95024a432ed12ad","observation_id":"44c4d96d-7540-4cd4-9298-5e47c0a08ae1","resolution":{"observed_at":"2026-08-12T13:09:48.347205Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2202.11214","last_updated":"2022-02-22T22:19:35Z","snapshot_observed_at":"2026-08-02T21:09:07.860947Z","submitted_at":"2022-02-22T22:19:35Z","title":"FourCastNet: A Global Data-driven High-resolution Weather Model using Adaptive Fourier Neural Operators","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2202.11214","snapshot_observed_at":"2026-08-12T13:09:48.155468Z","title":"Fourcastnet: A global data-driven high-resolution weather model using adaptive fourier neural operators,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2411.16439","last_updated":"2024-11-25T14:40:04Z","snapshot_observed_at":"2026-08-12T13:04:13.120869Z","submitted_at":"2024-11-25T14:40:04Z","title":"Generalizable Deep Learning Approach for 3D Particle Imaging using Holographic Microscopy","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-12T13:09:48.155468Z"},"links":{"cited_paper":"/paper/2202.11214","citing_paper":"/paper/2411.16439"},"observation_digest":"sha256:fab86c78c0d9169101690af5580c41fa2a79c36698fe302990e5c4f768dc8237","observation_id":"54c13561-d3b3-45b1-8aa7-a7c92a368d3a","resolution":{"observed_at":"2026-08-12T13:09:48.155468Z","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":"2026-08-12T13:09:48.321555Z","title":"Binary cross entropy with deep learning technique for image classification,","venue":null,"work_id":"a4a48bfe-15f5-419a-aa49-0b91a5151eae","year":2020},"citing_paper":{"arxiv_id":"2411.16439","last_updated":"2024-11-25T14:40:04Z","snapshot_observed_at":"2026-08-12T13:04:13.120869Z","submitted_at":"2024-11-25T14:40:04Z","title":"Generalizable Deep Learning Approach for 3D Particle Imaging using Holographic Microscopy","version":1},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-12T13:09:48.161912Z"},"links":{"citing_paper":"/paper/2411.16439"},"observation_digest":"sha256:699ab4fcc9161155119a266557f8f726ea708c6eeb6264b76b509435a0ec25f0","observation_id":"a822c92f-b247-4dd0-87c4-266c83e95336","resolution":{"observed_at":"2026-08-12T13:09:48.327301Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-12T13:09:48.304101Z","title":"Digital holographic microscope for measuring three-dimensional particle distributions and motions,","venue":null,"work_id":"94d9f263-4ac5-45da-9bdb-4b952a027de9","year":2006},"citing_paper":{"arxiv_id":"2411.16439","last_updated":"2024-11-25T14:40:04Z","snapshot_observed_at":"2026-08-12T13:04:13.120869Z","submitted_at":"2024-11-25T14:40:04Z","title":"Generalizable Deep Learning Approach for 3D Particle Imaging using Holographic Microscopy","version":1},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-12T13:09:48.167264Z"},"links":{"citing_paper":"/paper/2411.16439"},"observation_digest":"sha256:81c3ccc6622cce9dfd811d97849afd41303c6d36ec01342059db8e8b0257d108","observation_id":"d61cd0f9-079e-4225-b153-0a01f88b8d2a","resolution":{"observed_at":"2026-08-12T13:09:48.309238Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-12T13:09:48.286504Z","title":"Digital holographic particle image velocimetry: eliminating a sign-ambiguity error and a bias error from the measured particle field displacement,","venue":null,"work_id":"16c75068-cf5b-4f54-b886-1019a9f45d86","year":2008},"citing_paper":{"arxiv_id":"2411.16439","last_updated":"2024-11-25T14:40:04Z","snapshot_observed_at":"2026-08-12T13:04:13.120869Z","submitted_at":"2024-11-25T14:40:04Z","title":"Generalizable Deep Learning Approach for 3D Particle Imaging using Holographic Microscopy","version":1},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-08-12T13:09:48.172258Z"},"links":{"citing_paper":"/paper/2411.16439"},"observation_digest":"sha256:b6bacdd919fa03967e6e2cae82033cd3495dc7cbc7c8c7ba1fe11393f2b3cca5","observation_id":"c0d769e4-2d09-4bf8-8705-78535485a6cf","resolution":{"observed_at":"2026-08-12T13:09:48.292058Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-12T13:09:48.269944Z","title":"Lagrangian particle tracking in three dimensions via single -camera in -line digital holography,","venue":null,"work_id":"bb4b7b37-5c36-4af2-b666-153f999ddb05","year":2008},"citing_paper":{"arxiv_id":"2411.16439","last_updated":"2024-11-25T14:40:04Z","snapshot_observed_at":"2026-08-12T13:04:13.120869Z","submitted_at":"2024-11-25T14:40:04Z","title":"Generalizable Deep Learning Approach for 3D Particle Imaging using Holographic Microscopy","version":1},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-08-12T13:09:48.177135Z"},"links":{"citing_paper":"/paper/2411.16439"},"observation_digest":"sha256:2e66e8e4b36525c3bff8f837edeacb7b36f7276f9406917fa8a20ea7bd56cd4a","observation_id":"3ee03e06-a81d-4925-8851-62ace34a1ff3","resolution":{"observed_at":"2026-08-12T13:09:48.275525Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-12T13:09:48.253954Z","title":"ANSI/ASAE S572.3","venue":null,"work_id":"8668bc79-f4a7-4f6c-98f3-bb6867b7f11d","year":2020},"citing_paper":{"arxiv_id":"2411.16439","last_updated":"2024-11-25T14:40:04Z","snapshot_observed_at":"2026-08-12T13:04:13.120869Z","submitted_at":"2024-11-25T14:40:04Z","title":"Generalizable Deep Learning Approach for 3D Particle Imaging using Holographic Microscopy","version":1},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-08-12T13:09:48.182090Z"},"links":{"citing_paper":"/paper/2411.16439"},"observation_digest":"sha256:5e5e4b73f4621595a1a96f668bce674ea21d9b44c66690495d099f8d1e156fc5","observation_id":"14d57d02-27ea-4850-89f8-ae1dd5e38c17","resolution":{"observed_at":"2026-08-12T13:09:48.259099Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-12T13:09:48.235091Z","title":"Characterization of biophysical interactions in the water column using in situ digital holography,","venue":null,"work_id":"07098de3-2aaa-4752-b128-f85059fd144c","year":2013},"citing_paper":{"arxiv_id":"2411.16439","last_updated":"2024-11-25T14:40:04Z","snapshot_observed_at":"2026-08-12T13:04:13.120869Z","submitted_at":"2024-11-25T14:40:04Z","title":"Generalizable Deep Learning Approach for 3D Particle Imaging using Holographic Microscopy","version":1},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-08-12T13:09:48.186963Z"},"links":{"citing_paper":"/paper/2411.16439"},"observation_digest":"sha256:86a5ff53f3d27468361e048a44617973db6ec0b4354841a06af6e96753e251bd","observation_id":"11f81f86-862e-426a-929b-720d9e4e5e27","resolution":{"observed_at":"2026-08-12T13:09:48.242471Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2411.16439","last_updated":"2024-11-25T14:40:04Z","latest_version":1,"primary_category":"physics.optics","snapshot_observed_at":"2026-08-12T13:04:13.120869Z","submitted_at":"2024-11-25T14:40:04Z","title":"Generalizable Deep Learning Approach for 3D Particle Imaging using Holographic Microscopy"},"reference_resolution":{"displayed":51,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":1,"verified_exact":0,"verified_fuzzy":50},"total_outbound_references":51},"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":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"thesis":"As of 13 August 2026, this Paper Citation Record lists 51 of 51 outbound references and 0 inbound Pith citation observations for arXiv:2411.16439."}