{"as_of":"2026-08-08T03:39:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:bf6527a0546ceec583b3907007c7b20364342b657f7c4101e362db66faed181b","coverage":[{"denominator":21,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":21,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T13:30:20.569910Z","state":"measured"},{"denominator":22,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":22,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-07T06:34:17.273281+00:00","state":"measured"},{"denominator":1,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":1,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-04T18:38:56.166142Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2505.21634","last_updated":"2025-05-27T18:07:06Z","snapshot_observed_at":"2026-08-07T13:23:50.933161Z","submitted_at":"2025-05-27T18:07:06Z","title":"Laparoscopic Image Desmoking Using the U-Net with New Loss Function and Integrated Differentiable Wiener Filter","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2505.21634","snapshot_observed_at":"2026-08-04T18:38:56.166142Z","title":"Laparoscopic Image Desmoking Using the U- Net with New Loss Function and Integrated Differentiable Wiener Filter","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2509.09849","last_updated":"2025-09-11T20:58:52Z","snapshot_observed_at":"2026-08-04T18:38:55.805422Z","submitted_at":"2025-09-11T20:58:52Z","title":"Investigating the Impact of Various Loss Functions and Learnable Wiener Filter for Laparoscopic Image Desmoking","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-04T18:38:56.166142Z"},"links":{"cited_paper":"/paper/2505.21634","citing_paper":"/paper/2509.09849"},"observation_digest":"sha256:a90e1226f244480e67e7b4171b3a031b67c6c33ac05316bb3bdc3f2da74f29c5","observation_id":"e1bb6ad6-b354-47fd-96a0-55a83ffec794","resolution":{"observed_at":"2026-08-04T18:38:56.166142Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2505.21634/citation-record","integrity":"/paper/2505.21634/integrity","json":"/paper/2505.21634/citation-record.json","paper":"/paper/2505.21634"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:30:24.300702Z","title":"Removal of smoke effects in laparoscopic surgery via adversarial neural network and the dark channel prior,","venue":null,"work_id":"02f4e72a-f960-4b92-8587-4e35b07d02f6","year":2022},"citing_paper":{"arxiv_id":"2505.21634","last_updated":"2025-05-27T18:07:06Z","snapshot_observed_at":"2026-08-07T13:23:50.933161Z","submitted_at":"2025-05-27T18:07:06Z","title":"Laparoscopic Image Desmoking Using the U-Net with New Loss Function and Integrated Differentiable Wiener Filter","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-07T13:30:18.475320Z"},"links":{"citing_paper":"/paper/2505.21634"},"observation_digest":"sha256:e1275d136ac42ad885ba1adf93ffe4bb61c317fb8843b5bc44cbc42ef2747d2d","observation_id":"a1565a55-ff17-485b-89ce-5fbade83a081","resolution":{"observed_at":"2026-08-07T13:30:24.377113Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:30:24.172785Z","title":"A new benchmark in vivo paired dataset for laparoscopic image de-smoking,","venue":null,"work_id":"642381db-c04c-4a1b-ba6a-d66321340b01","year":2024},"citing_paper":{"arxiv_id":"2505.21634","last_updated":"2025-05-27T18:07:06Z","snapshot_observed_at":"2026-08-07T13:23:50.933161Z","submitted_at":"2025-05-27T18:07:06Z","title":"Laparoscopic Image Desmoking Using the U-Net with New Loss Function and Integrated Differentiable Wiener Filter","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-07T13:30:18.558150Z"},"links":{"citing_paper":"/paper/2505.21634"},"observation_digest":"sha256:d9e81ff17632becd6c042320ddec9c61ada7389594e72966a6563851216350ae","observation_id":"15ca30d8-56b9-4197-b497-7ee297bbfa3d","resolution":{"observed_at":"2026-08-07T13:30:24.237723Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:30:23.997860Z","title":"Desmoke-lap: improved unpaired image-to-image translation for desmoking in laparoscopic surgery,","venue":null,"work_id":"27597db0-3bce-4252-8d4f-f714a0780727","year":2022},"citing_paper":{"arxiv_id":"2505.21634","last_updated":"2025-05-27T18:07:06Z","snapshot_observed_at":"2026-08-07T13:23:50.933161Z","submitted_at":"2025-05-27T18:07:06Z","title":"Laparoscopic Image Desmoking Using the U-Net with New Loss Function and Integrated Differentiable Wiener Filter","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-07T13:30:18.659560Z"},"links":{"citing_paper":"/paper/2505.21634"},"observation_digest":"sha256:e34c64c3a860f89e6610a0d021798b4a3802baccafb76ec012cf8d8dc4a485c7","observation_id":"56ee79b9-d189-46b7-b5b1-3885a1159e70","resolution":{"observed_at":"2026-08-07T13:30:24.071746Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:30:23.830588Z","title":"Interpretable automatic rosacea detection with whitened cosine similarity,","venue":null,"work_id":"e2a2f899-984f-4be5-89c3-0183c785fdb7","year":2025},"citing_paper":{"arxiv_id":"2505.21634","last_updated":"2025-05-27T18:07:06Z","snapshot_observed_at":"2026-08-07T13:23:50.933161Z","submitted_at":"2025-05-27T18:07:06Z","title":"Laparoscopic Image Desmoking Using the U-Net with New Loss Function and Integrated Differentiable Wiener Filter","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-07T13:30:18.772371Z"},"links":{"citing_paper":"/paper/2505.21634"},"observation_digest":"sha256:fc763e0ea81bd09ca8a514979b2ea1abbc2bd6f5ed00acc3ee6ecb18d890048c","observation_id":"29883670-54bd-41d7-abf0-6e9cc2ff5373","resolution":{"observed_at":"2026-08-07T13:30:23.932762Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:30:23.675074Z","title":"Skin disease detection using deep learning,","venue":null,"work_id":"312773bd-5c1c-439e-bf75-2721b4b50f67","year":2023},"citing_paper":{"arxiv_id":"2505.21634","last_updated":"2025-05-27T18:07:06Z","snapshot_observed_at":"2026-08-07T13:23:50.933161Z","submitted_at":"2025-05-27T18:07:06Z","title":"Laparoscopic Image Desmoking Using the U-Net with New Loss Function and Integrated Differentiable Wiener Filter","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-07T13:30:18.833016Z"},"links":{"citing_paper":"/paper/2505.21634"},"observation_digest":"sha256:a1d67991bd029a60c486ba25f7510eec74d1d7367eb7f1ad114f8ea1b53273ec","observation_id":"6b3e8a2e-ed5b-4cdb-8ba7-813a33135587","resolution":{"observed_at":"2026-08-07T13:30:23.736060Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:30:23.413716Z","title":"Increasing rosacea awareness among population using deep learning and statistical approaches,","venue":null,"work_id":"2c987672-5ec7-4583-9ba6-042d2a39e2c2","year":2024},"citing_paper":{"arxiv_id":"2505.21634","last_updated":"2025-05-27T18:07:06Z","snapshot_observed_at":"2026-08-07T13:23:50.933161Z","submitted_at":"2025-05-27T18:07:06Z","title":"Laparoscopic Image Desmoking Using the U-Net with New Loss Function and Integrated Differentiable Wiener Filter","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-07T13:30:18.881424Z"},"links":{"citing_paper":"/paper/2505.21634"},"observation_digest":"sha256:380018d8fb44f2a64d91830ab0388bf18bf6ef90ca89f4dfa84b74a65f734d46","observation_id":"310ae733-5126-4ccf-a0d6-e1ae49d0fa30","resolution":{"observed_at":"2026-08-07T13:30:23.514903Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-07T13:30:18.949348Z","title":"U-net: Convolutional networks for biomedical image segmentation,","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2505.21634","last_updated":"2025-05-27T18:07:06Z","snapshot_observed_at":"2026-08-07T13:23:50.933161Z","submitted_at":"2025-05-27T18:07:06Z","title":"Laparoscopic Image Desmoking Using the U-Net with New Loss Function and Integrated Differentiable Wiener Filter","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-07T13:30:18.949348Z"},"links":{"citing_paper":"/paper/2505.21634"},"observation_digest":"sha256:fa91ad726a7773d2c945982968e8ad9d962c011c1822d0af5dc76fa0c346fc78","observation_id":"0b60cf2d-0b1f-4b89-bf6f-cd227c76bac4","resolution":{"observed_at":"2026-08-07T13:30:18.949348Z","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":"2026-08-07T13:30:23.135940Z","title":"Deep wiener deconvolution: Wiener meets deep learning for image deblurring,","venue":null,"work_id":"8b3c8c41-7fb8-4183-8685-39e91924fabd","year":2020},"citing_paper":{"arxiv_id":"2505.21634","last_updated":"2025-05-27T18:07:06Z","snapshot_observed_at":"2026-08-07T13:23:50.933161Z","submitted_at":"2025-05-27T18:07:06Z","title":"Laparoscopic Image Desmoking Using the U-Net with New Loss Function and Integrated Differentiable Wiener Filter","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-07T13:30:19.009531Z"},"links":{"citing_paper":"/paper/2505.21634"},"observation_digest":"sha256:34e33cc7de12fc2dcba010e153b40571238214c0fbd2ea2e4f16f8c52427692b","observation_id":"645d1453-887e-428a-9e25-5f63c20d3da2","resolution":{"observed_at":"2026-08-07T13:30:23.217632Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-07T13:30:19.104861Z","title":"Loss functions for image restoration with neural networks,","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2505.21634","last_updated":"2025-05-27T18:07:06Z","snapshot_observed_at":"2026-08-07T13:23:50.933161Z","submitted_at":"2025-05-27T18:07:06Z","title":"Laparoscopic Image Desmoking Using the U-Net with New Loss Function and Integrated Differentiable Wiener Filter","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-07T13:30:19.104861Z"},"links":{"citing_paper":"/paper/2505.21634"},"observation_digest":"sha256:224c7cd57601d62a3c51be87597966c1ff811df772a8cfbc72f5d3664fc1c60e","observation_id":"b2657e23-7db7-48cf-a70a-c5701ec51c75","resolution":{"observed_at":"2026-08-07T13:30:19.104861Z","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":"2026-08-07T13:30:22.806702Z","title":"Perceptual losses for real-time style transfer and super-resolution,","venue":null,"work_id":"f3aa1c96-6403-4d49-bb3e-f51622af6bf9","year":2016},"citing_paper":{"arxiv_id":"2505.21634","last_updated":"2025-05-27T18:07:06Z","snapshot_observed_at":"2026-08-07T13:23:50.933161Z","submitted_at":"2025-05-27T18:07:06Z","title":"Laparoscopic Image Desmoking Using the U-Net with New Loss Function and Integrated Differentiable Wiener Filter","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-07T13:30:19.213301Z"},"links":{"citing_paper":"/paper/2505.21634"},"observation_digest":"sha256:f1da288a3baa1463faa66690b2e8bb7dc4b27936a9f59174972dffc03570fb3e","observation_id":"bd64fe18-e825-4e68-83e0-4c0e2fdd1fa0","resolution":{"observed_at":"2026-08-07T13:30:22.895093Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-07T13:30:19.359857Z","title":"Single image haze removal using dark channel prior,","venue":null,"work_id":null,"year":2010},"citing_paper":{"arxiv_id":"2505.21634","last_updated":"2025-05-27T18:07:06Z","snapshot_observed_at":"2026-08-07T13:23:50.933161Z","submitted_at":"2025-05-27T18:07:06Z","title":"Laparoscopic Image Desmoking Using the U-Net with New Loss Function and Integrated Differentiable Wiener Filter","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-07T13:30:19.359857Z"},"links":{"citing_paper":"/paper/2505.21634"},"observation_digest":"sha256:ce16e3c13b54608730fb8a61b01d89a159812a2539719283cf9d18b9b606a4ea","observation_id":"4d03c7c8-38a1-44e3-9f92-8f52abb55527","resolution":{"observed_at":"2026-08-07T13:30:19.359857Z","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":"2026-08-07T13:30:22.557651Z","title":"Generative smoke removal,","venue":null,"work_id":"1de5fee3-5790-4cec-b100-6b1dc60b1bdd","year":2020},"citing_paper":{"arxiv_id":"2505.21634","last_updated":"2025-05-27T18:07:06Z","snapshot_observed_at":"2026-08-07T13:23:50.933161Z","submitted_at":"2025-05-27T18:07:06Z","title":"Laparoscopic Image Desmoking Using the U-Net with New Loss Function and Integrated Differentiable Wiener Filter","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-07T13:30:19.446242Z"},"links":{"citing_paper":"/paper/2505.21634"},"observation_digest":"sha256:5d3dc250b724b20d5a45c0fe0045320e84f5106a3d4b5e090dd6bad8176b969c","observation_id":"cb78980f-b773-4499-9bde-78dbef7da87a","resolution":{"observed_at":"2026-08-07T13:30:22.672039Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:30:22.325244Z","title":"Multi-stages de-smoking model based on cyclegan for surgical de-smoking,","venue":null,"work_id":"1431cca8-fd32-48cb-b06c-bf4bd81bfa50","year":2023},"citing_paper":{"arxiv_id":"2505.21634","last_updated":"2025-05-27T18:07:06Z","snapshot_observed_at":"2026-08-07T13:23:50.933161Z","submitted_at":"2025-05-27T18:07:06Z","title":"Laparoscopic Image Desmoking Using the U-Net with New Loss Function and Integrated Differentiable Wiener Filter","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-07T13:30:19.545872Z"},"links":{"citing_paper":"/paper/2505.21634"},"observation_digest":"sha256:1cefe4f975083c441307de7bdac527cc48bcfdf74e9807cfa6dd065335814ca3","observation_id":"3e43ba1b-0b7d-4435-be36-499d144e0c6a","resolution":{"observed_at":"2026-08-07T13:30:22.379647Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:30:22.036895Z","title":"Desmoking laparoscopy surgery images using an image-to-image translation guided by an embedded dark channel,","venue":null,"work_id":"9548cfb7-ee60-438b-8d49-926728cb0896","year":2020},"citing_paper":{"arxiv_id":"2505.21634","last_updated":"2025-05-27T18:07:06Z","snapshot_observed_at":"2026-08-07T13:23:50.933161Z","submitted_at":"2025-05-27T18:07:06Z","title":"Laparoscopic Image Desmoking Using the U-Net with New Loss Function and Integrated Differentiable Wiener Filter","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-07T13:30:19.666518Z"},"links":{"citing_paper":"/paper/2505.21634"},"observation_digest":"sha256:d50fb7a1d22576355aa3aebe26e319d3510d9f870cf67213c66ab31573eac3a6","observation_id":"3e9ecb3a-237f-484d-888c-30b396b79f3c","resolution":{"observed_at":"2026-08-07T13:30:22.078233Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:30:21.740087Z","title":"Vision transformers for single image dehazing,","venue":null,"work_id":"4a29fd86-c37c-4171-aec1-00f12330f69c","year":1927},"citing_paper":{"arxiv_id":"2505.21634","last_updated":"2025-05-27T18:07:06Z","snapshot_observed_at":"2026-08-07T13:23:50.933161Z","submitted_at":"2025-05-27T18:07:06Z","title":"Laparoscopic Image Desmoking Using the U-Net with New Loss Function and Integrated Differentiable Wiener Filter","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-07T13:30:19.803206Z"},"links":{"citing_paper":"/paper/2505.21634"},"observation_digest":"sha256:f36751997814942832d8cfd26d92495361cab27cfc2cc61ceab53a4529e5c2d6","observation_id":"874df568-edca-4d83-a9db-faccb73953d9","resolution":{"observed_at":"2026-08-07T13:30:21.833267Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:30:21.503110Z","title":"Medical image segmentation review: The success of u-net,","venue":null,"work_id":"a5db61e1-12a9-430b-9bb4-c2fe86b02a52","year":2024},"citing_paper":{"arxiv_id":"2505.21634","last_updated":"2025-05-27T18:07:06Z","snapshot_observed_at":"2026-08-07T13:23:50.933161Z","submitted_at":"2025-05-27T18:07:06Z","title":"Laparoscopic Image Desmoking Using the U-Net with New Loss Function and Integrated Differentiable Wiener Filter","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-07T13:30:19.965063Z"},"links":{"citing_paper":"/paper/2505.21634"},"observation_digest":"sha256:f990d8ba3a07830087df7451b43a0112472d2d1247156615a9623c0a86053962","observation_id":"8cd25e21-2714-401a-830c-7051e18ed3f1","resolution":{"observed_at":"2026-08-07T13:30:21.608454Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:30:21.312483Z","title":null,"venue":null,"work_id":"edf2e81d-145b-4e7c-a307-853715938d13","year":1987},"citing_paper":{"arxiv_id":"2505.21634","last_updated":"2025-05-27T18:07:06Z","snapshot_observed_at":"2026-08-07T13:23:50.933161Z","submitted_at":"2025-05-27T18:07:06Z","title":"Laparoscopic Image Desmoking Using the U-Net with New Loss Function and Integrated Differentiable Wiener Filter","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-07T13:30:20.039421Z"},"links":{"citing_paper":"/paper/2505.21634"},"observation_digest":"sha256:27d82e7508f9751d2d751330ab75b62d3caf7402577394ee556abc5b8bb0c628","observation_id":"884ec2c1-ff48-4588-a18d-b45e76146a18","resolution":{"observed_at":"2026-08-07T13:30:21.385316Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:30:21.133701Z","title":"Evaluation of ssim loss function in rir generator gans,","venue":null,"work_id":"447d87d8-33cc-437f-8bda-6d3c2de6aee2","year":2024},"citing_paper":{"arxiv_id":"2505.21634","last_updated":"2025-05-27T18:07:06Z","snapshot_observed_at":"2026-08-07T13:23:50.933161Z","submitted_at":"2025-05-27T18:07:06Z","title":"Laparoscopic Image Desmoking Using the U-Net with New Loss Function and Integrated Differentiable Wiener Filter","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-07T13:30:20.160456Z"},"links":{"citing_paper":"/paper/2505.21634"},"observation_digest":"sha256:7b619c1752ad7731311bef513270d10bfa4ed79fc01b7cc78934016117394707","observation_id":"05a0b2f8-77f6-4166-b492-6b6eca5d521e","resolution":{"observed_at":"2026-08-07T13:30:21.168574Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:30:20.870815Z","title":"Comparison of the cielab and ciede2000 color difference formulas,","venue":null,"work_id":"4c221416-f530-4677-8856-8484e6ac2d42","year":2016},"citing_paper":{"arxiv_id":"2505.21634","last_updated":"2025-05-27T18:07:06Z","snapshot_observed_at":"2026-08-07T13:23:50.933161Z","submitted_at":"2025-05-27T18:07:06Z","title":"Laparoscopic Image Desmoking Using the U-Net with New Loss Function and Integrated Differentiable Wiener Filter","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-07T13:30:20.280598Z"},"links":{"citing_paper":"/paper/2505.21634"},"observation_digest":"sha256:7d4bc31cd99054495499de07da5378b269c8b703f81d6254fa8412934e4bdd4e","observation_id":"a317ea47-3ec5-42d6-9117-e0e9b7f8e9d2","resolution":{"observed_at":"2026-08-07T13:30:20.966531Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1409.1556","last_updated":"2015-04-10T16:25:04Z","snapshot_observed_at":"2026-07-06T03:53:32.549552Z","submitted_at":"2014-09-04T19:48:04Z","title":"Very Deep Convolutional Networks for Large-Scale Image Recognition","version":6},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1409.1556","snapshot_observed_at":"2026-08-07T13:30:20.445028Z","title":"Very deep convolutional networks for large-scale image recognition,","venue":null,"work_id":null,"year":2014},"citing_paper":{"arxiv_id":"2505.21634","last_updated":"2025-05-27T18:07:06Z","snapshot_observed_at":"2026-08-07T13:23:50.933161Z","submitted_at":"2025-05-27T18:07:06Z","title":"Laparoscopic Image Desmoking Using the U-Net with New Loss Function and Integrated Differentiable Wiener Filter","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-07T13:30:20.445028Z"},"links":{"cited_paper":"/paper/1409.1556","citing_paper":"/paper/2505.21634"},"observation_digest":"sha256:6acf60a9dbc0b6f15b3de37ef7157daef2d8bea796097885f4428e2961bd4699","observation_id":"28949980-1a70-4307-9f52-5673ec9f28ad","resolution":{"observed_at":"2026-08-07T13:30:20.445028Z","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":"2026-08-07T13:30:20.569910Z","title":"Image-to-image translation with conditional adversarial networks,","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2505.21634","last_updated":"2025-05-27T18:07:06Z","snapshot_observed_at":"2026-08-07T13:23:50.933161Z","submitted_at":"2025-05-27T18:07:06Z","title":"Laparoscopic Image Desmoking Using the U-Net with New Loss Function and Integrated Differentiable Wiener Filter","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-07T13:30:20.569910Z"},"links":{"citing_paper":"/paper/2505.21634"},"observation_digest":"sha256:2b67589b78a1858396e650090882b3853940a2bbea9fe82f88bad370777c048a","observation_id":"910304d8-3df8-411d-bc4d-e9f20d5d2a2f","resolution":{"observed_at":"2026-08-07T13:30:20.569910Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2505.21634","last_updated":"2025-05-27T18:07:06Z","latest_version":1,"primary_category":"eess.IV","snapshot_observed_at":"2026-08-07T13:23:50.933161Z","submitted_at":"2025-05-27T18:07:06Z","title":"Laparoscopic Image Desmoking Using the U-Net with New Loss Function and Integrated Differentiable Wiener Filter"},"reference_resolution":{"displayed":21,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":6,"verified_exact":0,"verified_fuzzy":15},"total_outbound_references":21},"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":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"thesis":"As of 8 August 2026, this Paper Citation Record lists 21 of 21 outbound references and 1 inbound Pith citation observation for arXiv:2505.21634."}