{"as_of":"2026-08-12T15:37:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:3b8fc5ae668495b515096c848b3f6b585489fb1e3fdd5c23d768c2155470dec5","coverage":[{"denominator":20,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":20,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-11T10:34:42.948985Z","state":"measured"},{"denominator":20,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":20,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-12T06:34:41.77262+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/2412.16499/citation-record","integrity":"/paper/2412.16499/integrity","json":"/paper/2412.16499/citation-record.json","paper":"/paper/2412.16499"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1007/s10921-022-","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T10:34:43.082144Z","title":null,"venue":null,"work_id":"2b944bfa-8a31-493e-b858-cc36029c3d02","year":2022},"citing_paper":{"arxiv_id":"2412.16499","last_updated":"2024-12-21T06:10:32Z","snapshot_observed_at":"2026-08-12T06:01:07.425612Z","submitted_at":"2024-12-21T06:10:32Z","title":"Autonomous Crack Detection using Deep Learning on Synthetic Thermogram Datasets","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-11T10:34:42.857361Z"},"links":{"citing_paper":"/paper/2412.16499"},"observation_digest":"sha256:fd4e024bd99ed2f6fb1a0c465dc2d70c5282725c82c6f5669f28aa4344cbaf65","observation_id":"ee28232f-64b1-4971-b1ac-c85b99b08b93","resolution":{"observed_at":"2026-08-11T10:34:43.087072Z","resolver_source":"doi_truncated","status":"malformed_identifier"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-11T10:34:43.281619Z","title":null,"venue":null,"work_id":"c0f18dd2-5b11-4d74-8cba-a3b85fc2002a","year":2019},"citing_paper":{"arxiv_id":"2412.16499","last_updated":"2024-12-21T06:10:32Z","snapshot_observed_at":"2026-08-12T06:01:07.425612Z","submitted_at":"2024-12-21T06:10:32Z","title":"Autonomous Crack Detection using Deep Learning on Synthetic Thermogram Datasets","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-11T10:34:42.862600Z"},"links":{"citing_paper":"/paper/2412.16499"},"observation_digest":"sha256:365352ba860ec26d4d3d88aa80c10d105f8efd4f027ab7f8440ff1762302bec1","observation_id":"dd5cb841-6bab-44fc-99c9-5530a8d1a116","resolution":{"observed_at":"2026-08-11T10:34:43.285576Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1016/j.aej.2017.01.020","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T10:34:43.065062Z","title":null,"venue":null,"work_id":"36b9b4b4-cdf0-4180-9c2e-f235a3783c20","year":2018},"citing_paper":{"arxiv_id":"2412.16499","last_updated":"2024-12-21T06:10:32Z","snapshot_observed_at":"2026-08-12T06:01:07.425612Z","submitted_at":"2024-12-21T06:10:32Z","title":"Autonomous Crack Detection using Deep Learning on Synthetic Thermogram Datasets","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-11T10:34:42.867294Z"},"links":{"citing_paper":"/paper/2412.16499"},"observation_digest":"sha256:674778da05c128785f7745f41a8bbe0aea906eb3cad7a3e23adceaa61e7da6ea","observation_id":"e71d4952-6b05-4d30-9b1f-3219f0222901","resolution":{"observed_at":"2026-08-11T10:34:43.070072Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1007/s12559-021-09922-w","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T10:34:43.049483Z","title":null,"venue":null,"work_id":"d1e04af2-179a-4a8a-8bd9-aca8d1163539","year":2021},"citing_paper":{"arxiv_id":"2412.16499","last_updated":"2024-12-21T06:10:32Z","snapshot_observed_at":"2026-08-12T06:01:07.425612Z","submitted_at":"2024-12-21T06:10:32Z","title":"Autonomous Crack Detection using Deep Learning on Synthetic Thermogram Datasets","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-11T10:34:42.872244Z"},"links":{"citing_paper":"/paper/2412.16499"},"observation_digest":"sha256:7d422cc6570c1832b3bc072870822abf4fd22f5fbe8c3522bdbba2fc459d513a","observation_id":"967209ff-9b7f-4214-8bec-876e78b5841b","resolution":{"observed_at":"2026-08-11T10:34:43.054199Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1007/s43503-","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T10:34:43.027602Z","title":null,"venue":null,"work_id":"4e699be8-3509-4f37-bdce-12d90e6e96ab","year":2022},"citing_paper":{"arxiv_id":"2412.16499","last_updated":"2024-12-21T06:10:32Z","snapshot_observed_at":"2026-08-12T06:01:07.425612Z","submitted_at":"2024-12-21T06:10:32Z","title":"Autonomous Crack Detection using Deep Learning on Synthetic Thermogram Datasets","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-11T10:34:42.877470Z"},"links":{"citing_paper":"/paper/2412.16499"},"observation_digest":"sha256:ba6d12598eae5655ebaf979d1e18c5bd062d385cbfc0ad12cf94d925e80c6b14","observation_id":"e636ddaa-056a-49bd-aed0-cdaedcd37ca7","resolution":{"observed_at":"2026-08-11T10:34:43.038717Z","resolver_source":"doi_truncated","status":"malformed_identifier"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.3390/s22239365","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T10:34:43.012575Z","title":"Deep Learning Based Infrared Thermal Image Analysis of Complex Pavement Defect Conditions Considering Seasonal Effect","venue":null,"work_id":"443a3240-83df-4cd7-b4de-fe4bed00fb44","year":2022},"citing_paper":{"arxiv_id":"2412.16499","last_updated":"2024-12-21T06:10:32Z","snapshot_observed_at":"2026-08-12T06:01:07.425612Z","submitted_at":"2024-12-21T06:10:32Z","title":"Autonomous Crack Detection using Deep Learning on Synthetic Thermogram Datasets","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-11T10:34:42.882670Z"},"links":{"citing_paper":"/paper/2412.16499"},"observation_digest":"sha256:0dac39d3032e3d1cf2d77c7b8301c6f82c5530a486b535da96794ac7af600008","observation_id":"c604b8a2-7337-40ee-ae8c-2e8df2c951d5","resolution":{"observed_at":"2026-08-11T10:34:43.017065Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1063/5.0020404","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T10:34:42.997823Z","title":null,"venue":null,"work_id":"1cc68616-715e-419c-a27b-1b9dbc897054","year":2020},"citing_paper":{"arxiv_id":"2412.16499","last_updated":"2024-12-21T06:10:32Z","snapshot_observed_at":"2026-08-12T06:01:07.425612Z","submitted_at":"2024-12-21T06:10:32Z","title":"Autonomous Crack Detection using Deep Learning on Synthetic Thermogram Datasets","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-11T10:34:42.888128Z"},"links":{"citing_paper":"/paper/2412.16499"},"observation_digest":"sha256:f0265986ab4a190a32d2c98b34d39fda1ebdeaca9ef721417fa4085bf40ae395","observation_id":"bf7ed8f9-04c0-4e85-ba02-0834a9222775","resolution":{"observed_at":"2026-08-11T10:34:43.002496Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[{"edge_observation":{"observed_at":"2026-08-11T12:17:59.062674+00:00","source":"paper_reference_links","state":"open"},"event_date":"2020-12-17","event_type":"correction","notice_doi":"10.1063/5.0035554","provenance":{"observed_at":"2026-07-11T03:09:00.854736+00:00","source":"crossref","source_record_id":"10.1063/5.0035554->10.1063/5.0020404:correction"}}],"reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.3390/bdcc5010009","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T10:34:42.979328Z","title":"Automatic Defects Segmen- tation and Identification by Deep Learning Algorithm with Pulsed Ther- mography: Synthetic and Experimental Data","venue":null,"work_id":"86685c13-a30f-4b5d-aacb-6b1cad03fbce","year":2021},"citing_paper":{"arxiv_id":"2412.16499","last_updated":"2024-12-21T06:10:32Z","snapshot_observed_at":"2026-08-12T06:01:07.425612Z","submitted_at":"2024-12-21T06:10:32Z","title":"Autonomous Crack Detection using Deep Learning on Synthetic Thermogram Datasets","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-11T10:34:42.892533Z"},"links":{"citing_paper":"/paper/2412.16499"},"observation_digest":"sha256:f399be640eb43fef1433c4273925864e00d97780e111113c09bd3da019d9184b","observation_id":"0ea84d4e-eeba-412c-87fd-ce31534216c6","resolution":{"observed_at":"2026-08-11T10:34:42.986715Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-11T10:34:43.267495Z","title":null,"venue":null,"work_id":"a6d69eb7-73f5-45e6-aeef-3fbd89e9b1b4","year":null},"citing_paper":{"arxiv_id":"2412.16499","last_updated":"2024-12-21T06:10:32Z","snapshot_observed_at":"2026-08-12T06:01:07.425612Z","submitted_at":"2024-12-21T06:10:32Z","title":"Autonomous Crack Detection using Deep Learning on Synthetic Thermogram Datasets","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-11T10:34:42.897146Z"},"links":{"citing_paper":"/paper/2412.16499"},"observation_digest":"sha256:6cd5a33e24838e6b2d153f5f9dd9715305bd50303b070dba76422d7952556659","observation_id":"5c202727-f0f2-4682-8626-f9249291bbdb","resolution":{"observed_at":"2026-08-11T10:34:43.272203Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-11T10:34:43.252406Z","title":null,"venue":null,"work_id":"b0b7092b-651d-4284-b510-68659cb985d1","year":null},"citing_paper":{"arxiv_id":"2412.16499","last_updated":"2024-12-21T06:10:32Z","snapshot_observed_at":"2026-08-12T06:01:07.425612Z","submitted_at":"2024-12-21T06:10:32Z","title":"Autonomous Crack Detection using Deep Learning on Synthetic Thermogram Datasets","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-11T10:34:42.901711Z"},"links":{"citing_paper":"/paper/2412.16499"},"observation_digest":"sha256:423ac704de761a9543111f485534bf7c7c508bf4e570a6d486e093568a982db0","observation_id":"5223d5f5-57e1-45aa-9f7b-24d500dc9553","resolution":{"observed_at":"2026-08-11T10:34:43.257477Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-11T10:34:43.236722Z","title":"J., & Shotton, J","venue":null,"work_id":"eeaa5b74-e05a-43cd-b0ca-a0e7b5f25b66","year":2021},"citing_paper":{"arxiv_id":"2412.16499","last_updated":"2024-12-21T06:10:32Z","snapshot_observed_at":"2026-08-12T06:01:07.425612Z","submitted_at":"2024-12-21T06:10:32Z","title":"Autonomous Crack Detection using Deep Learning on Synthetic Thermogram Datasets","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-11T10:34:42.907039Z"},"links":{"citing_paper":"/paper/2412.16499"},"observation_digest":"sha256:d96303a5757dcbc99862bd14a6fb440762134f7a179e080541782c0899763343","observation_id":"65dced64-6761-4e81-a89c-f38098d2f2e1","resolution":{"observed_at":"2026-08-11T10:34:43.242294Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2210.07574","last_updated":"2023-02-15T06:26:38Z","snapshot_observed_at":"2026-08-12T10:47:09.554460Z","submitted_at":"2022-10-14T06:54:24Z","title":"Is synthetic data from generative models ready for image recognition?","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2210.07574","snapshot_observed_at":"2026-08-11T10:34:42.911407Z","title":null,"venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2412.16499","last_updated":"2024-12-21T06:10:32Z","snapshot_observed_at":"2026-08-12T06:01:07.425612Z","submitted_at":"2024-12-21T06:10:32Z","title":"Autonomous Crack Detection using Deep Learning on Synthetic Thermogram Datasets","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-11T10:34:42.911407Z"},"links":{"cited_paper":"/paper/2210.07574","citing_paper":"/paper/2412.16499"},"observation_digest":"sha256:b79b8d7ca8772a6e5cc42e01a8370b1981596918dea51dca97fc3c84e79ac26f","observation_id":"91776a6a-e230-48a4-9f27-d838befc6bab","resolution":{"observed_at":"2026-08-11T10:34:42.911407Z","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":"2026-08-11T10:34:43.221782Z","title":null,"venue":null,"work_id":"8108853b-469c-4877-95ca-b3cd29a75771","year":2021},"citing_paper":{"arxiv_id":"2412.16499","last_updated":"2024-12-21T06:10:32Z","snapshot_observed_at":"2026-08-12T06:01:07.425612Z","submitted_at":"2024-12-21T06:10:32Z","title":"Autonomous Crack Detection using Deep Learning on Synthetic Thermogram Datasets","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-11T10:34:42.916552Z"},"links":{"citing_paper":"/paper/2412.16499"},"observation_digest":"sha256:475b9689653752ac9a11ff20533af9709bc376c225b76afe63f177e1fd71617c","observation_id":"cf4c09b2-e830-4b15-8bf6-8932aea96f2c","resolution":{"observed_at":"2026-08-11T10:34:43.226696Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-11T10:34:43.204680Z","title":null,"venue":null,"work_id":"0e8126d0-6a22-4afa-b021-97d5e6253616","year":2021},"citing_paper":{"arxiv_id":"2412.16499","last_updated":"2024-12-21T06:10:32Z","snapshot_observed_at":"2026-08-12T06:01:07.425612Z","submitted_at":"2024-12-21T06:10:32Z","title":"Autonomous Crack Detection using Deep Learning on Synthetic Thermogram Datasets","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-11T10:34:42.921290Z"},"links":{"citing_paper":"/paper/2412.16499"},"observation_digest":"sha256:e8f84dcfaaac8d18b4d3e3d15b9c7f71dd2f6875d3b1a3594f72ed7a55a9bfe7","observation_id":"313e8399-243c-43f6-9eb3-f08881521e8d","resolution":{"observed_at":"2026-08-11T10:34:43.210045Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-11T10:34:43.188454Z","title":null,"venue":null,"work_id":"3d432022-4e37-4ab2-b168-2aa5406d0fbd","year":2021},"citing_paper":{"arxiv_id":"2412.16499","last_updated":"2024-12-21T06:10:32Z","snapshot_observed_at":"2026-08-12T06:01:07.425612Z","submitted_at":"2024-12-21T06:10:32Z","title":"Autonomous Crack Detection using Deep Learning on Synthetic Thermogram Datasets","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-11T10:34:42.925826Z"},"links":{"citing_paper":"/paper/2412.16499"},"observation_digest":"sha256:b6dfe3826d17d47942f94ba23da2d6b04cb0758c925e461c0f8724ab1174a68b","observation_id":"90a9ec1e-4491-4d80-8ca7-5dd8fa183bed","resolution":{"observed_at":"2026-08-11T10:34:43.193215Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2302.04062","last_updated":"2025-04-04T09:34:37Z","snapshot_observed_at":"2026-08-12T06:00:51.338678Z","submitted_at":"2023-02-08T13:59:31Z","title":"Machine Learning for Synthetic Data Generation: A Review","version":10},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2302.04062","snapshot_observed_at":"2026-08-11T10:34:42.930043Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2412.16499","last_updated":"2024-12-21T06:10:32Z","snapshot_observed_at":"2026-08-12T06:01:07.425612Z","submitted_at":"2024-12-21T06:10:32Z","title":"Autonomous Crack Detection using Deep Learning on Synthetic Thermogram Datasets","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-11T10:34:42.930043Z"},"links":{"cited_paper":"/paper/2302.04062","citing_paper":"/paper/2412.16499"},"observation_digest":"sha256:fa4a0007e51c9ba5b87a164853fcc19748a9a4362462e93472c068b98ea1b189","observation_id":"c3e88610-012c-4dfb-9fc2-ed70d884fe31","resolution":{"observed_at":"2026-08-11T10:34:42.930043Z","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":"2026-08-11T10:34:43.173493Z","title":"A., Paczan, N., Webb, R., & Susskind, J","venue":null,"work_id":"7d270130-8259-4718-9be3-d56cac34fba0","year":2021},"citing_paper":{"arxiv_id":"2412.16499","last_updated":"2024-12-21T06:10:32Z","snapshot_observed_at":"2026-08-12T06:01:07.425612Z","submitted_at":"2024-12-21T06:10:32Z","title":"Autonomous Crack Detection using Deep Learning on Synthetic Thermogram Datasets","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-11T10:34:42.934761Z"},"links":{"citing_paper":"/paper/2412.16499"},"observation_digest":"sha256:e55875f9eae6aa00417fae880aff250281131dc109d3569b48d324a727da8043","observation_id":"f93ee2c0-23da-466e-9139-972773a7de1d","resolution":{"observed_at":"2026-08-11T10:34:43.178234Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-11T10:34:43.157977Z","title":null,"venue":null,"work_id":"8bb0b2d3-d4f0-48c5-b4e4-0f46c7ca76fd","year":2022},"citing_paper":{"arxiv_id":"2412.16499","last_updated":"2024-12-21T06:10:32Z","snapshot_observed_at":"2026-08-12T06:01:07.425612Z","submitted_at":"2024-12-21T06:10:32Z","title":"Autonomous Crack Detection using Deep Learning on Synthetic Thermogram Datasets","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-11T10:34:42.939496Z"},"links":{"citing_paper":"/paper/2412.16499"},"observation_digest":"sha256:7d51bcd7992306d87e325e0108634e6f9b18b01ed974239646b8297f9908ce0d","observation_id":"d0bb822c-ed65-4bbc-9965-970c7d4cf6e9","resolution":{"observed_at":"2026-08-11T10:34:43.162755Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-11T10:34:43.143197Z","title":null,"venue":null,"work_id":"384e7cc8-ad65-48e5-b63a-743cb88519f7","year":2021},"citing_paper":{"arxiv_id":"2412.16499","last_updated":"2024-12-21T06:10:32Z","snapshot_observed_at":"2026-08-12T06:01:07.425612Z","submitted_at":"2024-12-21T06:10:32Z","title":"Autonomous Crack Detection using Deep Learning on Synthetic Thermogram Datasets","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-11T10:34:42.943943Z"},"links":{"citing_paper":"/paper/2412.16499"},"observation_digest":"sha256:b9657fe4fa23fcf5603ec4c97ec805769816530a6bc6d6457142dfe739aa2d19","observation_id":"4052bba7-905b-494c-a0b9-153e92ae1d5f","resolution":{"observed_at":"2026-08-11T10:34:43.147853Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-11T10:34:43.127981Z","title":null,"venue":null,"work_id":"d891e39c-9593-4ad2-85ad-2ede58d08267","year":2022},"citing_paper":{"arxiv_id":"2412.16499","last_updated":"2024-12-21T06:10:32Z","snapshot_observed_at":"2026-08-12T06:01:07.425612Z","submitted_at":"2024-12-21T06:10:32Z","title":"Autonomous Crack Detection using Deep Learning on Synthetic Thermogram Datasets","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-11T10:34:42.948985Z"},"links":{"citing_paper":"/paper/2412.16499"},"observation_digest":"sha256:aa05cafaaf3b14f0b7c02ad780a0834214bf6d913c5519313f9d5888ffdc6979","observation_id":"beec12ad-47aa-446f-9e8e-bd050f03a828","resolution":{"observed_at":"2026-08-11T10:34:43.132621Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2412.16499","last_updated":"2024-12-21T06:10:32Z","latest_version":1,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-12T06:01:07.425612Z","submitted_at":"2024-12-21T06:10:32Z","title":"Autonomous Crack Detection using Deep Learning on Synthetic Thermogram Datasets"},"reference_resolution":{"displayed":20,"state_counts":{"malformed_identifier":2,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":11,"verified_exact":5,"verified_fuzzy":2},"total_outbound_references":20},"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":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"thesis":"As of 12 August 2026, this Paper Citation Record lists 20 of 20 outbound references and 0 inbound Pith citation observations for arXiv:2412.16499."}