{"as_of":"2026-08-18T18:42:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:1ef9af00c416e7d3f0515987fc79acc34b6e2e8b5d35ebb4c6a3139da96cff06","coverage":[{"denominator":56,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":56,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-11T23:07:00.747597Z","state":"measured"},{"denominator":59,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":59,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-18T06:34:40.430872+00:00","state":"measured"},{"denominator":3,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":3,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-16T04:18:29.273909Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"pith","source_observed_at":"2026-07-04T13:49:51.240969Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2412.02831","last_updated":"2026-06-28T17:16:26Z","snapshot_observed_at":"2026-08-14T04:47:19.489944Z","submitted_at":"2024-12-03T20:53:42Z","title":"FLAME 3 Dataset: Unleashing the Power of Radiometric Thermal UAV Imagery for Wildfire Management","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2412.02831","snapshot_observed_at":"2026-08-16T04:18:29.273909Z","title":"Available: https://arxiv.org/abs/2412.02831","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2505.01638","last_updated":"2025-05-03T00:23:11Z","snapshot_observed_at":"2026-08-17T11:42:11.229213Z","submitted_at":"2025-05-03T00:23:11Z","title":"Seeing Heat with Color -- RGB-Only Wildfire Temperature Inference from SAM-Guided Multimodal Distillation using Radiometric Ground Truth","version":1},"reference_index":2024,"source":"pdf_text","source_observed_at":"2026-08-16T04:18:29.273909Z"},"links":{"cited_paper":"/paper/2412.02831","citing_paper":"/paper/2505.01638"},"observation_digest":"sha256:6d889b516c0a990031e94173cec89a5e3c1c8d16b442d0c907286c3a2358dbb5","observation_id":"2378761d-0163-4c1a-a94c-971f7b8d2918","resolution":{"observed_at":"2026-08-16T04:18:29.273909Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2412.02831","last_updated":"2026-06-28T17:16:26Z","snapshot_observed_at":"2026-08-14T04:47:19.489944Z","submitted_at":"2024-12-03T20:53:42Z","title":"FLAME 3 Dataset: Unleashing the Power of Radiometric Thermal UAV Imagery for Wildfire Management","version":2},"cited_work":{"arxiv_id":"2412.02831","doi":null,"metadata_source":"pith","pith_arxiv_id":"2412.02831","snapshot_observed_at":"2026-07-04T13:49:51.240969Z","title":"Flame 3 dataset: Unleashing the power of radiometric thermal uav imagery for wildfire man- agement","venue":"cs.CV","work_id":"00ae87ab-4df5-41c5-baab-891db0e9fb88","year":2024},"citing_paper":{"arxiv_id":"2604.20190","last_updated":"2026-04-22T05:11:02Z","snapshot_observed_at":"2026-07-31T09:36:22.924731Z","submitted_at":"2026-04-22T05:11:02Z","title":"WildFireVQA: A Large-Scale Radiometric Thermal VQA Benchmark for Aerial Wildfire Monitoring","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-05-10T01:08:34.674972Z"},"links":{"cited_paper":"/paper/2412.02831","citing_paper":"/paper/2604.20190"},"observation_digest":"sha256:43e1c7a40e0c3fb04226894d7d211ab8f161c36326708c4195077d8ceedfd17e","observation_id":"42fc68a1-b911-4bac-a132-d46e1d670e82","resolution":{"observed_at":"2026-06-30T02:16:06.837937Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.02831","last_updated":"2026-06-28T17:16:26Z","snapshot_observed_at":"2026-08-14T04:47:19.489944Z","submitted_at":"2024-12-03T20:53:42Z","title":"FLAME 3 Dataset: Unleashing the Power of Radiometric Thermal UAV Imagery for Wildfire Management","version":2},"cited_work":{"arxiv_id":"2412.02831","doi":null,"metadata_source":"pith","pith_arxiv_id":"2412.02831","snapshot_observed_at":"2026-07-04T13:49:51.240969Z","title":"Flame 3 dataset: Unleashing the power of radiometric thermal uav imagery for wildfire man- agement","venue":"cs.CV","work_id":"00ae87ab-4df5-41c5-baab-891db0e9fb88","year":2024},"citing_paper":{"arxiv_id":"2606.27128","last_updated":"2026-06-25T15:06:59Z","snapshot_observed_at":"2026-08-16T18:56:12.947686Z","submitted_at":"2026-06-25T15:06:59Z","title":"FlameVQA: A Physically-Grounded UAV Wildfire VQA Benchmark with Radiometric Thermal Supervision","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-06-26T04:56:43.756842Z"},"links":{"cited_paper":"/paper/2412.02831","citing_paper":"/paper/2606.27128"},"observation_digest":"sha256:5a0c29b63aabbd6fd3715757109edb13aa3c468de21e0addd039bb78de35306d","observation_id":"5a967ff1-e8dd-4dae-b4eb-477043a76f1e","resolution":{"observed_at":"2026-07-04T13:49:51.242481Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2412.02831/citation-record","integrity":"/paper/2412.02831/integrity","json":"/paper/2412.02831/citation-record.json","paper":"/paper/2412.02831"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:07:01.296993Z","title":"Flame 3 computer vision subset (sycan marsh),","venue":null,"work_id":"22bf940f-5e82-4eb1-8a2e-ec97a408f165","year":2024},"citing_paper":{"arxiv_id":"2412.02831","last_updated":"2026-06-28T17:16:26Z","snapshot_observed_at":"2026-08-14T04:47:19.489944Z","submitted_at":"2024-12-03T20:53:42Z","title":"FLAME 3 Dataset: Unleashing the Power of Radiometric Thermal UAV Imagery for Wildfire Management","version":2},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-11T23:07:00.606163Z"},"links":{"citing_paper":"/paper/2412.02831"},"observation_digest":"sha256:809421580f3061fe548847905edb7d51c15e86fc14c672c3eb1e5d5e00dfb146","observation_id":"20f4edbe-b2b1-4aff-a1da-890c21c3bafe","resolution":{"observed_at":"2026-08-11T23:07:01.299354Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"dsv/8724543","doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:07:00.977531Z","title":"Flame 3 -nadir thermal fire image dataset,","venue":null,"work_id":"7e5a1637-ac1f-420b-a959-36fe8f307b87","year":2024},"citing_paper":{"arxiv_id":"2412.02831","last_updated":"2026-06-28T17:16:26Z","snapshot_observed_at":"2026-08-14T04:47:19.489944Z","submitted_at":"2024-12-03T20:53:42Z","title":"FLAME 3 Dataset: Unleashing the Power of Radiometric Thermal UAV Imagery for Wildfire Management","version":2},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-11T23:07:00.609523Z"},"links":{"citing_paper":"/paper/2412.02831"},"observation_digest":"sha256:90819a6ecf96f17304dddfbb80ad3e681a5b8d516f1dcba50d38e82c86c337f6","observation_id":"2817373b-8c28-4351-963a-54a72f4ebb8d","resolution":{"observed_at":"2026-08-11T23:07:00.981488Z","resolver_source":"raw_fallback","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-11T23:07:01.289585Z","title":"A comprehensive survey of research towards ai-enabled unmanned aerial systems in pre-, active-, and post-wildfire management,","venue":null,"work_id":"fe7b5acf-806c-448e-9712-e4ba9c5da629","year":2024},"citing_paper":{"arxiv_id":"2412.02831","last_updated":"2026-06-28T17:16:26Z","snapshot_observed_at":"2026-08-14T04:47:19.489944Z","submitted_at":"2024-12-03T20:53:42Z","title":"FLAME 3 Dataset: Unleashing the Power of Radiometric Thermal UAV Imagery for Wildfire Management","version":2},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-11T23:07:00.612435Z"},"links":{"citing_paper":"/paper/2412.02831"},"observation_digest":"sha256:5181bf3d631c8650e0586905b8b98d45418b1b84c17371e1e98c343dab2508a1","observation_id":"06bc5e0c-810c-4c91-a985-a2435d4dd639","resolution":{"observed_at":"2026-08-11T23:07:01.292782Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-11T23:07:01.282154Z","title":"UA VS-FDDB: UA Vs- based Forest Fire Detection Database,","venue":null,"work_id":"2ff15825-c24e-46d6-9339-faec161ac20e","year":2024},"citing_paper":{"arxiv_id":"2412.02831","last_updated":"2026-06-28T17:16:26Z","snapshot_observed_at":"2026-08-14T04:47:19.489944Z","submitted_at":"2024-12-03T20:53:42Z","title":"FLAME 3 Dataset: Unleashing the Power of Radiometric Thermal UAV Imagery for Wildfire Management","version":2},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-11T23:07:00.615203Z"},"links":{"citing_paper":"/paper/2412.02831"},"observation_digest":"sha256:7815d2947c2f6e30468e1538f3c175847f01cf9a59b6033c63a42ee5981ad7e4","observation_id":"6687fdd1-3090-481f-9b25-67b4a067efe9","resolution":{"observed_at":"2026-08-11T23:07:01.284855Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-11T23:07:01.275003Z","title":"A rgb-thermal based adaptive modality learning network for day–night wildfire identification,","venue":null,"work_id":"55f3ba54-ef7f-4c88-8548-4c35c983088e","year":2023},"citing_paper":{"arxiv_id":"2412.02831","last_updated":"2026-06-28T17:16:26Z","snapshot_observed_at":"2026-08-14T04:47:19.489944Z","submitted_at":"2024-12-03T20:53:42Z","title":"FLAME 3 Dataset: Unleashing the Power of Radiometric Thermal UAV Imagery for Wildfire Management","version":2},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-11T23:07:00.617957Z"},"links":{"citing_paper":"/paper/2412.02831"},"observation_digest":"sha256:8eb7ebd110965d37c1d5f7a2be5154efc31ddcf199b003247104947c80f54831","observation_id":"0621edc1-5291-4411-83b1-fcc59b9e3959","resolution":{"observed_at":"2026-08-11T23:07:01.277845Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-11T23:07:01.267897Z","title":"RGB-thermal wildfire dataset,","venue":null,"work_id":"fc57f37a-b5b6-4714-955f-e4bd230df6b6","year":2022},"citing_paper":{"arxiv_id":"2412.02831","last_updated":"2026-06-28T17:16:26Z","snapshot_observed_at":"2026-08-14T04:47:19.489944Z","submitted_at":"2024-12-03T20:53:42Z","title":"FLAME 3 Dataset: Unleashing the Power of Radiometric Thermal UAV Imagery for Wildfire Management","version":2},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-11T23:07:00.620827Z"},"links":{"citing_paper":"/paper/2412.02831"},"observation_digest":"sha256:92b5c9cd5e17599d97c858b1c78773a51860733d05c58fd98085f86e49b44ad3","observation_id":"25fe4324-96fa-4bf3-bde4-1b29794d10dd","resolution":{"observed_at":"2026-08-11T23:07:01.270445Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-11T23:07:01.260579Z","title":"Fire and smoke dataset,","venue":null,"work_id":"023e4528-900a-46cd-bd40-6aa170178958","year":2021},"citing_paper":{"arxiv_id":"2412.02831","last_updated":"2026-06-28T17:16:26Z","snapshot_observed_at":"2026-08-14T04:47:19.489944Z","submitted_at":"2024-12-03T20:53:42Z","title":"FLAME 3 Dataset: Unleashing the Power of Radiometric Thermal UAV Imagery for Wildfire Management","version":2},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-11T23:07:00.623656Z"},"links":{"citing_paper":"/paper/2412.02831"},"observation_digest":"sha256:043682c3592b8cacc26371ec6c77a8b691a78dd695658813c936227bf2f3d6d5","observation_id":"db3685f5-3095-4670-a06b-78d2272d35f5","resolution":{"observed_at":"2026-08-11T23:07:01.263397Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-11T23:07:01.253158Z","title":"Wildfire detection image data,","venue":null,"work_id":"000d7ece-0640-4ddd-a45a-f0b3cb832396","year":2021},"citing_paper":{"arxiv_id":"2412.02831","last_updated":"2026-06-28T17:16:26Z","snapshot_observed_at":"2026-08-14T04:47:19.489944Z","submitted_at":"2024-12-03T20:53:42Z","title":"FLAME 3 Dataset: Unleashing the Power of Radiometric Thermal UAV Imagery for Wildfire Management","version":2},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-11T23:07:00.625978Z"},"links":{"citing_paper":"/paper/2412.02831"},"observation_digest":"sha256:a13a8770693f5aa4b2553a5799554c8b21d0cdd77f651262979bb517832403b8","observation_id":"c12cc487-9b1f-4348-bcff-fb16c68f9dcd","resolution":{"observed_at":"2026-08-11T23:07:01.255908Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-11T23:07:00.628202Z","title":"Emergencynet: Efficient aerial image classification for drone-based emergency monitoring using atrous con- volutional feature fusion,","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2412.02831","last_updated":"2026-06-28T17:16:26Z","snapshot_observed_at":"2026-08-14T04:47:19.489944Z","submitted_at":"2024-12-03T20:53:42Z","title":"FLAME 3 Dataset: Unleashing the Power of Radiometric Thermal UAV Imagery for Wildfire Management","version":2},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-11T23:07:00.628202Z"},"links":{"citing_paper":"/paper/2412.02831"},"observation_digest":"sha256:5174f9aba1c0d55fa993c2fd1f736b84c73a9e051b3d57b391d9f4e1d724bac0","observation_id":"9dbae06d-b382-415f-9e3c-d01d87504dcb","resolution":{"observed_at":"2026-08-11T23:07:00.628202Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1906.08716","last_updated":"2019-06-20T16:03:32Z","snapshot_observed_at":"2026-08-12T20:57:35.008555Z","submitted_at":"2019-06-20T16:03:32Z","title":"Deep-Learning-Based Aerial Image Classification for Emergency Response Applications Using Unmanned Aerial Vehicles","version":1},"cited_work":{"arxiv_id":"1906.08716","doi":null,"metadata_source":"pith","pith_arxiv_id":"1906.08716","snapshot_observed_at":"2026-08-11T23:07:00.904347Z","title":"Deep-Learning-Based Aerial Image Classification for Emergency Response Applications Using Unmanned Aerial Vehicles","venue":"cs.CV","work_id":"c9659096-d78c-459c-8d0d-afa9b0be9561","year":2019},"citing_paper":{"arxiv_id":"2412.02831","last_updated":"2026-06-28T17:16:26Z","snapshot_observed_at":"2026-08-14T04:47:19.489944Z","submitted_at":"2024-12-03T20:53:42Z","title":"FLAME 3 Dataset: Unleashing the Power of Radiometric Thermal UAV Imagery for Wildfire Management","version":2},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-11T23:07:00.630322Z"},"links":{"cited_paper":"/paper/1906.08716","citing_paper":"/paper/2412.02831"},"observation_digest":"sha256:1944c4562f5e5250a538b7d6d1f82848bcdc559b096c456e63e4e968f1e2b28f","observation_id":"0e133ec9-d14b-4999-9d24-dcc5b557126c","resolution":{"observed_at":"2026-08-11T23:07:00.907602Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-11T23:07:01.242064Z","title":"Dataset for forest fire detection,","venue":null,"work_id":"bf79baf9-e746-4f66-b617-d59e72b814bd","year":2020},"citing_paper":{"arxiv_id":"2412.02831","last_updated":"2026-06-28T17:16:26Z","snapshot_observed_at":"2026-08-14T04:47:19.489944Z","submitted_at":"2024-12-03T20:53:42Z","title":"FLAME 3 Dataset: Unleashing the Power of Radiometric Thermal UAV Imagery for Wildfire Management","version":2},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-11T23:07:00.632797Z"},"links":{"citing_paper":"/paper/2412.02831"},"observation_digest":"sha256:37324125ff8f80fe8c6fdb3718a812c778d9e800d0856dbb2e7d9566debcfbd1","observation_id":"e4fb0197-03c7-48dc-bf46-ec48314a6521","resolution":{"observed_at":"2026-08-11T23:07:01.244698Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-11T23:07:01.235284Z","title":"Fire detection,","venue":null,"work_id":"750c9e1b-d47f-4f29-969d-27532bf8a9c9","year":2020},"citing_paper":{"arxiv_id":"2412.02831","last_updated":"2026-06-28T17:16:26Z","snapshot_observed_at":"2026-08-14T04:47:19.489944Z","submitted_at":"2024-12-03T20:53:42Z","title":"FLAME 3 Dataset: Unleashing the Power of Radiometric Thermal UAV Imagery for Wildfire Management","version":2},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-11T23:07:00.634856Z"},"links":{"citing_paper":"/paper/2412.02831"},"observation_digest":"sha256:41fc3ccf018341c44426b03306e861370125e6849dfae6c366476ee906fad962","observation_id":"ca4c5f4f-28a2-4ea3-87fa-114287254d7e","resolution":{"observed_at":"2026-08-11T23:07:01.237930Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-11T23:07:01.228106Z","title":"FireNET,","venue":null,"work_id":"732ff8ca-eb70-44a6-a353-00f623ce9721","year":2019},"citing_paper":{"arxiv_id":"2412.02831","last_updated":"2026-06-28T17:16:26Z","snapshot_observed_at":"2026-08-14T04:47:19.489944Z","submitted_at":"2024-12-03T20:53:42Z","title":"FLAME 3 Dataset: Unleashing the Power of Radiometric Thermal UAV Imagery for Wildfire Management","version":2},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-11T23:07:00.637016Z"},"links":{"citing_paper":"/paper/2412.02831"},"observation_digest":"sha256:c4db9565171cb7f0d0a2ba98a202ed45abd07cac03ac5f210922b4ba07e816a8","observation_id":"22dca443-2256-48ec-b66e-9d258a39c83d","resolution":{"observed_at":"2026-08-11T23:07:01.230624Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-11T23:07:01.221125Z","title":"Fire Detection from CCTV,","venue":null,"work_id":"e708bb11-c2cc-45e0-9b92-434b6cb3fb78","year":2019},"citing_paper":{"arxiv_id":"2412.02831","last_updated":"2026-06-28T17:16:26Z","snapshot_observed_at":"2026-08-14T04:47:19.489944Z","submitted_at":"2024-12-03T20:53:42Z","title":"FLAME 3 Dataset: Unleashing the Power of Radiometric Thermal UAV Imagery for Wildfire Management","version":2},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-11T23:07:00.639107Z"},"links":{"citing_paper":"/paper/2412.02831"},"observation_digest":"sha256:f098b894cc5c7332d5c3bf458255f07a2f4f2d15d3981e7bbe649d9075780f6a","observation_id":"f336a1e6-d34c-401c-8136-c31d0afca362","resolution":{"observed_at":"2026-08-11T23:07:01.223752Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-11T23:07:01.214367Z","title":"Experimental exploration of compact convolutional neural network architectures for non-temporal real-time fire detection,","venue":null,"work_id":"9add930a-9d4c-4c2e-bee0-b6306862a0f9","year":2019},"citing_paper":{"arxiv_id":"2412.02831","last_updated":"2026-06-28T17:16:26Z","snapshot_observed_at":"2026-08-14T04:47:19.489944Z","submitted_at":"2024-12-03T20:53:42Z","title":"FLAME 3 Dataset: Unleashing the Power of Radiometric Thermal UAV Imagery for Wildfire Management","version":2},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-11T23:07:00.641121Z"},"links":{"citing_paper":"/paper/2412.02831"},"observation_digest":"sha256:8cd9a381ebdb0fed512d0e55de61116e7ccf77ee449febde5c6c3ad7e5035678","observation_id":"7312287a-fe6f-425a-85b8-36e027c43b5c","resolution":{"observed_at":"2026-08-11T23:07:01.216750Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-11T23:07:01.207948Z","title":"Experimentally defined convolutional nerual network architecture variants for non-temporal real-time fire detection,","venue":null,"work_id":"e1bee272-8373-4e48-828e-39cfc476b03d","year":2018},"citing_paper":{"arxiv_id":"2412.02831","last_updated":"2026-06-28T17:16:26Z","snapshot_observed_at":"2026-08-14T04:47:19.489944Z","submitted_at":"2024-12-03T20:53:42Z","title":"FLAME 3 Dataset: Unleashing the Power of Radiometric Thermal UAV Imagery for Wildfire Management","version":2},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-11T23:07:00.643490Z"},"links":{"citing_paper":"/paper/2412.02831"},"observation_digest":"sha256:dad2da7434392db7455c1e5e768006b133617d96f63e9c1be924344966a92411","observation_id":"01946190-46fd-4738-aa19-04784eed6364","resolution":{"observed_at":"2026-08-11T23:07:01.210416Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-11T23:07:01.201890Z","title":"Fire detection image dataset,","venue":null,"work_id":"01724a72-735c-4fd7-8ce2-f0cb433f04af","year":2017},"citing_paper":{"arxiv_id":"2412.02831","last_updated":"2026-06-28T17:16:26Z","snapshot_observed_at":"2026-08-14T04:47:19.489944Z","submitted_at":"2024-12-03T20:53:42Z","title":"FLAME 3 Dataset: Unleashing the Power of Radiometric Thermal UAV Imagery for Wildfire Management","version":2},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-11T23:07:00.645587Z"},"links":{"citing_paper":"/paper/2412.02831"},"observation_digest":"sha256:596aa69a3a971654dbc18840e319e4fa19b1528d7c422ba6b1784e0029c63672","observation_id":"c64dbe55-7cdd-44f9-b4da-289963df5b4f","resolution":{"observed_at":"2026-08-11T23:07:01.203988Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-11T23:07:01.195361Z","title":"Computer vision for wildfire research: An evolving image dataset for processing and analysis,","venue":null,"work_id":"a5757754-817f-45d8-b8db-db52261b65b4","year":2017},"citing_paper":{"arxiv_id":"2412.02831","last_updated":"2026-06-28T17:16:26Z","snapshot_observed_at":"2026-08-14T04:47:19.489944Z","submitted_at":"2024-12-03T20:53:42Z","title":"FLAME 3 Dataset: Unleashing the Power of Radiometric Thermal UAV Imagery for Wildfire Management","version":2},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-11T23:07:00.648204Z"},"links":{"citing_paper":"/paper/2412.02831"},"observation_digest":"sha256:6de0c7a94bcacf2e79a3a8338a6f284a0cd6904bd9c7aebb70dd27c4e4ef3f38","observation_id":"a8a0dbd0-a616-4f8d-b7b9-3c548b32b296","resolution":{"observed_at":"2026-08-11T23:07:01.197992Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-11T23:07:01.188059Z","title":"Real-time fire detection for video surveillance applications using a combination of experts based on color, shape and motion,","venue":null,"work_id":"a3fef9d4-d056-4067-879a-c43d9634e6f5","year":2015},"citing_paper":{"arxiv_id":"2412.02831","last_updated":"2026-06-28T17:16:26Z","snapshot_observed_at":"2026-08-14T04:47:19.489944Z","submitted_at":"2024-12-03T20:53:42Z","title":"FLAME 3 Dataset: Unleashing the Power of Radiometric Thermal UAV Imagery for Wildfire Management","version":2},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-11T23:07:00.651102Z"},"links":{"citing_paper":"/paper/2412.02831"},"observation_digest":"sha256:b38748028151ab2c1b766fe7a1a308b48a85d9e0910a376d5f764609353b6c92","observation_id":"8558572e-dcd9-4124-809b-ff962ff81db9","resolution":{"observed_at":"2026-08-11T23:07:01.190879Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-11T23:07:01.180581Z","title":"Improving fire detection reli- ability by a combination of videoanalytics,","venue":null,"work_id":"33f9ab0e-1b1d-49f7-97bd-8696780b2733","year":2014},"citing_paper":{"arxiv_id":"2412.02831","last_updated":"2026-06-28T17:16:26Z","snapshot_observed_at":"2026-08-14T04:47:19.489944Z","submitted_at":"2024-12-03T20:53:42Z","title":"FLAME 3 Dataset: Unleashing the Power of Radiometric Thermal UAV Imagery for Wildfire Management","version":2},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-11T23:07:00.654020Z"},"links":{"citing_paper":"/paper/2412.02831"},"observation_digest":"sha256:d4b57913f21c763df8358edce57dc96ac82949b8afc1716b1f099172320b3fba","observation_id":"aaa97ca7-8c5a-4ae3-859b-2d7b313ca339","resolution":{"observed_at":"2026-08-11T23:07:01.183775Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-11T23:07:01.173534Z","title":"Aerial imagery pile burn detection using deep learning: The flame dataset,","venue":null,"work_id":"d876b194-e4fb-4a2e-b8c2-aeabf29fb6ed","year":2021},"citing_paper":{"arxiv_id":"2412.02831","last_updated":"2026-06-28T17:16:26Z","snapshot_observed_at":"2026-08-14T04:47:19.489944Z","submitted_at":"2024-12-03T20:53:42Z","title":"FLAME 3 Dataset: Unleashing the Power of Radiometric Thermal UAV Imagery for Wildfire Management","version":2},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-11T23:07:00.656637Z"},"links":{"citing_paper":"/paper/2412.02831"},"observation_digest":"sha256:868ead38c779016c2d7a219380a246176545d237541be645edf302310db1e78f","observation_id":"e23b3306-dd36-4dd7-bc3d-192c599bb7e2","resolution":{"observed_at":"2026-08-11T23:07:01.176266Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-11T23:07:01.166468Z","title":"Shamsoshoara and F","venue":null,"work_id":"8c222fc0-5635-4d81-bc5d-2b7b805748f5","year":2023},"citing_paper":{"arxiv_id":"2412.02831","last_updated":"2026-06-28T17:16:26Z","snapshot_observed_at":"2026-08-14T04:47:19.489944Z","submitted_at":"2024-12-03T20:53:42Z","title":"FLAME 3 Dataset: Unleashing the Power of Radiometric Thermal UAV Imagery for Wildfire Management","version":2},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-11T23:07:00.661842Z"},"links":{"citing_paper":"/paper/2412.02831"},"observation_digest":"sha256:547abad64c9aba6ee77977379b54ce026eeda3fb6b438bf9a9481a1c96bc65a9","observation_id":"c86d7b6f-9ee4-49f4-aff1-d1f3aa5a38ab","resolution":{"observed_at":"2026-08-11T23:07:01.169148Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-11T23:07:01.159163Z","title":"Building a virtual reality fire environment based on fire dynamic simulator,","venue":null,"work_id":"4953277e-7fa6-4e42-9d2d-00b4025e4814","year":2020},"citing_paper":{"arxiv_id":"2412.02831","last_updated":"2026-06-28T17:16:26Z","snapshot_observed_at":"2026-08-14T04:47:19.489944Z","submitted_at":"2024-12-03T20:53:42Z","title":"FLAME 3 Dataset: Unleashing the Power of Radiometric Thermal UAV Imagery for Wildfire Management","version":2},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-11T23:07:00.664678Z"},"links":{"citing_paper":"/paper/2412.02831"},"observation_digest":"sha256:808e6f6bf64558381c1d8c4abba8c9a5178cdce7607496c8b051c978690e1dee","observation_id":"5afe0eba-218b-43d9-87f2-db1fc3a94352","resolution":{"observed_at":"2026-08-11T23:07:01.161875Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-11T23:07:01.151523Z","title":"Fluid dynamics of wildfires Once a wildfire is ignited, complex interactions with the local winds affect how it behaves","venue":null,"work_id":"6380162f-1ea0-456e-8871-f915239b7213","year":2019},"citing_paper":{"arxiv_id":"2412.02831","last_updated":"2026-06-28T17:16:26Z","snapshot_observed_at":"2026-08-14T04:47:19.489944Z","submitted_at":"2024-12-03T20:53:42Z","title":"FLAME 3 Dataset: Unleashing the Power of Radiometric Thermal UAV Imagery for Wildfire Management","version":2},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-11T23:07:00.667271Z"},"links":{"citing_paper":"/paper/2412.02831"},"observation_digest":"sha256:3d5c767a1bdeb99506068d13919acc4f31875f035fb25c30531d5b6859e46ce1","observation_id":"83599f29-100d-47ae-b66b-99c2a826bafd","resolution":{"observed_at":"2026-08-11T23:07:01.154470Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-11T23:07:01.144334Z","title":"Using a computational fluid dynamic model to guide wildland fire management,","venue":null,"work_id":"5473c599-85e3-4dae-a1af-af0c34aca151","year":2019},"citing_paper":{"arxiv_id":"2412.02831","last_updated":"2026-06-28T17:16:26Z","snapshot_observed_at":"2026-08-14T04:47:19.489944Z","submitted_at":"2024-12-03T20:53:42Z","title":"FLAME 3 Dataset: Unleashing the Power of Radiometric Thermal UAV Imagery for Wildfire Management","version":2},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-11T23:07:00.669702Z"},"links":{"citing_paper":"/paper/2412.02831"},"observation_digest":"sha256:46594b1d5d26da953d3e4ffee75b6b109f9deb7e6d4686e7bfa30fccaa9ce762","observation_id":"0f455652-8753-4696-a71d-13d9f7a1ce4c","resolution":{"observed_at":"2026-08-11T23:07:01.147213Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-11T23:07:01.137164Z","title":"Real-time flame segmentation based on RGB-thermal fusion,","venue":null,"work_id":"f25ee180-5995-46b4-a635-21536441377c","year":2021},"citing_paper":{"arxiv_id":"2412.02831","last_updated":"2026-06-28T17:16:26Z","snapshot_observed_at":"2026-08-14T04:47:19.489944Z","submitted_at":"2024-12-03T20:53:42Z","title":"FLAME 3 Dataset: Unleashing the Power of Radiometric Thermal UAV Imagery for Wildfire Management","version":2},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-11T23:07:00.672215Z"},"links":{"citing_paper":"/paper/2412.02831"},"observation_digest":"sha256:a5f9ac6ef4c0abfdcdbe8f24bf7ab3386edeccf4229468ad58a3a8c5efa3c20f","observation_id":"b0c0e486-c3c9-4ee7-b771-3fe223a0c546","resolution":{"observed_at":"2026-08-11T23:07:01.139963Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-11T23:07:01.128799Z","title":"Wuunet: Advanced fully convo- lutional neural network for multiclass fire segmentation,","venue":null,"work_id":"9b1c8107-6f08-4204-8ab7-a43681529361","year":2021},"citing_paper":{"arxiv_id":"2412.02831","last_updated":"2026-06-28T17:16:26Z","snapshot_observed_at":"2026-08-14T04:47:19.489944Z","submitted_at":"2024-12-03T20:53:42Z","title":"FLAME 3 Dataset: Unleashing the Power of Radiometric Thermal UAV Imagery for Wildfire Management","version":2},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-11T23:07:00.674797Z"},"links":{"citing_paper":"/paper/2412.02831"},"observation_digest":"sha256:e44b69c7e13cc59de5d46de38ebe98550a06d8b2998ee898f84c65a154b48ca5","observation_id":"21bc376a-92b9-4f58-b0d2-adaaa47fcb88","resolution":{"observed_at":"2026-08-11T23:07:01.132573Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-11T23:07:01.120936Z","title":"A model for the simulation of forest fire dynamics using cellular automata,","venue":null,"work_id":"86893f64-51e6-4397-942b-420647b882e1","year":2006},"citing_paper":{"arxiv_id":"2412.02831","last_updated":"2026-06-28T17:16:26Z","snapshot_observed_at":"2026-08-14T04:47:19.489944Z","submitted_at":"2024-12-03T20:53:42Z","title":"FLAME 3 Dataset: Unleashing the Power of Radiometric Thermal UAV Imagery for Wildfire Management","version":2},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-11T23:07:00.677337Z"},"links":{"citing_paper":"/paper/2412.02831"},"observation_digest":"sha256:bfab97d70769ac6137795007d9775277bce3a33e626d51035c7862b63825850c","observation_id":"34003715-8c38-4611-b236-48e5b5e76384","resolution":{"observed_at":"2026-08-11T23:07:01.123458Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-11T23:07:01.113867Z","title":"Learning-based prediction of wildfire spread with real-time rate of spread measurement,","venue":null,"work_id":"5b5edd59-ea50-49a0-83e0-aeb8fa5058e8","year":2020},"citing_paper":{"arxiv_id":"2412.02831","last_updated":"2026-06-28T17:16:26Z","snapshot_observed_at":"2026-08-14T04:47:19.489944Z","submitted_at":"2024-12-03T20:53:42Z","title":"FLAME 3 Dataset: Unleashing the Power of Radiometric Thermal UAV Imagery for Wildfire Management","version":2},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-11T23:07:00.679983Z"},"links":{"citing_paper":"/paper/2412.02831"},"observation_digest":"sha256:449ba5ca16e007ebb962b501e7d7be6c6f352665a7b4e5fd24f1ee9ab94fdb95","observation_id":"5ec870ba-2e2a-40e9-b7d7-2d7f0d7e5a19","resolution":{"observed_at":"2026-08-11T23:07:01.116868Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-11T23:07:01.106741Z","title":"An FPGA processor for modelling wildfire spreading,","venue":null,"work_id":"11b2236d-9945-42a4-b6a8-aa2d89994088","year":2013},"citing_paper":{"arxiv_id":"2412.02831","last_updated":"2026-06-28T17:16:26Z","snapshot_observed_at":"2026-08-14T04:47:19.489944Z","submitted_at":"2024-12-03T20:53:42Z","title":"FLAME 3 Dataset: Unleashing the Power of Radiometric Thermal UAV Imagery for Wildfire Management","version":2},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-11T23:07:00.682442Z"},"links":{"citing_paper":"/paper/2412.02831"},"observation_digest":"sha256:2743ea727d9dd047968cac21fb22d49cf3c051d1495bb93b08cee1666a6b8c72","observation_id":"742e42a1-2bca-4b3a-94f0-4b30bcbd4ecf","resolution":{"observed_at":"2026-08-11T23:07:01.109417Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-11T23:07:01.099869Z","title":"Use of spatially refined remote sensing fire detection data to initialize and evaluate coupled weather-wildfire growth model simulations,","venue":null,"work_id":"d81d4b4a-da92-41a6-80cc-09e46ba3441f","year":2013},"citing_paper":{"arxiv_id":"2412.02831","last_updated":"2026-06-28T17:16:26Z","snapshot_observed_at":"2026-08-14T04:47:19.489944Z","submitted_at":"2024-12-03T20:53:42Z","title":"FLAME 3 Dataset: Unleashing the Power of Radiometric Thermal UAV Imagery for Wildfire Management","version":2},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-11T23:07:00.684759Z"},"links":{"citing_paper":"/paper/2412.02831"},"observation_digest":"sha256:41a7bb2858ffcc641d7cb4c81776b73befe0f6ec59afb99fa1474261b0acccac","observation_id":"ff9dca99-1a3a-4306-b9fb-d62dee2b5c4f","resolution":{"observed_at":"2026-08-11T23:07:01.102594Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-11T23:07:01.092652Z","title":"Improving spatial resolution in exchange of temporal resolution in aliased image sequences,","venue":null,"work_id":"8d2faa20-9cb3-4423-b374-5c3b417d389b","year":1999},"citing_paper":{"arxiv_id":"2412.02831","last_updated":"2026-06-28T17:16:26Z","snapshot_observed_at":"2026-08-14T04:47:19.489944Z","submitted_at":"2024-12-03T20:53:42Z","title":"FLAME 3 Dataset: Unleashing the Power of Radiometric Thermal UAV Imagery for Wildfire Management","version":2},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-11T23:07:00.687212Z"},"links":{"citing_paper":"/paper/2412.02831"},"observation_digest":"sha256:9e3360fcbd194f5566c4b88807e795a0ff3478ddce6132768932f9650f6a63ad","observation_id":"cf002d1a-6957-49fd-88a1-578c63b7f155","resolution":{"observed_at":"2026-08-11T23:07:01.095392Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.21227/qad6-r683","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:07:00.775025Z","title":"The FLAME dataset: Aerial imagery pile burn detection using drones (uavs),","venue":null,"work_id":"52b8510c-0b70-401c-b66d-538785c9f753","year":2020},"citing_paper":{"arxiv_id":"2412.02831","last_updated":"2026-06-28T17:16:26Z","snapshot_observed_at":"2026-08-14T04:47:19.489944Z","submitted_at":"2024-12-03T20:53:42Z","title":"FLAME 3 Dataset: Unleashing the Power of Radiometric Thermal UAV Imagery for Wildfire Management","version":2},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-11T23:07:00.689712Z"},"links":{"citing_paper":"/paper/2412.02831"},"observation_digest":"sha256:414dc1187861efa77bb4309484dc7c8565383b57741c4933becffddaedb3cfaf","observation_id":"1c387c84-d2b9-4b76-b096-b810eddcc56e","resolution":{"observed_at":"2026-08-11T23:07:00.778677Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2204.10266","last_updated":"2022-04-21T17:06:57Z","snapshot_observed_at":"2026-08-17T13:56:20.588099Z","submitted_at":"2022-04-21T17:06:57Z","title":"DooDLeNet: Double DeepLab Enhanced Feature Fusion for Thermal-color Semantic Segmentation","version":1},"cited_work":{"arxiv_id":"2204.10266","doi":null,"metadata_source":"pith","pith_arxiv_id":"2204.10266","snapshot_observed_at":"2026-08-11T23:07:00.894570Z","title":"DooDLeNet: Double DeepLab Enhanced Feature Fusion for Thermal-color Semantic Segmentation","venue":"cs.LG","work_id":"41e30189-aa9e-4c84-be38-fe3e758bd5bf","year":2022},"citing_paper":{"arxiv_id":"2412.02831","last_updated":"2026-06-28T17:16:26Z","snapshot_observed_at":"2026-08-14T04:47:19.489944Z","submitted_at":"2024-12-03T20:53:42Z","title":"FLAME 3 Dataset: Unleashing the Power of Radiometric Thermal UAV Imagery for Wildfire Management","version":2},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-11T23:07:00.692220Z"},"links":{"cited_paper":"/paper/2204.10266","citing_paper":"/paper/2412.02831"},"observation_digest":"sha256:c71e96e549a42f6e3139a5e53a6023328a154f195f61c9563957280159e8eef9","observation_id":"0c10e100-26df-4e37-9e55-15f126757633","resolution":{"observed_at":"2026-08-11T23:07:00.897881Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2110.08988","last_updated":"2021-10-18T02:43:41Z","snapshot_observed_at":"2026-08-16T17:48:35.775996Z","submitted_at":"2021-10-18T02:43:41Z","title":"FEANet: Feature-Enhanced Attention Network for RGB-Thermal Real-time Semantic Segmentation","version":1},"cited_work":{"arxiv_id":"2110.08988","doi":null,"metadata_source":"pith","pith_arxiv_id":"2110.08988","snapshot_observed_at":"2026-08-11T23:07:00.884473Z","title":"FEANet: Feature-Enhanced Attention Network for RGB-Thermal Real-time Semantic Segmentation","venue":"cs.CV","work_id":"37da9f56-a72e-4d8e-a0b5-f8982b7f3c7d","year":2021},"citing_paper":{"arxiv_id":"2412.02831","last_updated":"2026-06-28T17:16:26Z","snapshot_observed_at":"2026-08-14T04:47:19.489944Z","submitted_at":"2024-12-03T20:53:42Z","title":"FLAME 3 Dataset: Unleashing the Power of Radiometric Thermal UAV Imagery for Wildfire Management","version":2},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-11T23:07:00.694997Z"},"links":{"cited_paper":"/paper/2110.08988","citing_paper":"/paper/2412.02831"},"observation_digest":"sha256:14bf9cdcc7440597cdf94fa35ea8feb1a6a0fa4a3c0204bda7add4845f6e4017","observation_id":"1fb8d9c0-81fc-402e-836e-a954d983d515","resolution":{"observed_at":"2026-08-11T23:07:00.887714Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.21227/swyw-6j78","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:07:00.783588Z","title":"FLAME 2: Fire detection and modeling: Aerial multi-spectral image dataset,","venue":null,"work_id":"7611de9c-b284-4d33-b29c-2d8007f71eb2","year":2022},"citing_paper":{"arxiv_id":"2412.02831","last_updated":"2026-06-28T17:16:26Z","snapshot_observed_at":"2026-08-14T04:47:19.489944Z","submitted_at":"2024-12-03T20:53:42Z","title":"FLAME 3 Dataset: Unleashing the Power of Radiometric Thermal UAV Imagery for Wildfire Management","version":2},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-11T23:07:00.697851Z"},"links":{"citing_paper":"/paper/2412.02831"},"observation_digest":"sha256:a3bb91af786875cddff6657809a5c5de212404eb9e900f7120f6ce32660eb9c5","observation_id":"654031d2-374e-4b31-bfa6-3d929c12950b","resolution":{"observed_at":"2026-08-11T23:07:00.786444Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-11T23:07:01.085531Z","title":"IC-GAN: An improved conditional generative adversarial network for RGB-to-IR image translation with applications to forest fire monitoring,","venue":null,"work_id":"436c314f-7b1e-458e-9253-abfa0fce8d7a","year":2023},"citing_paper":{"arxiv_id":"2412.02831","last_updated":"2026-06-28T17:16:26Z","snapshot_observed_at":"2026-08-14T04:47:19.489944Z","submitted_at":"2024-12-03T20:53:42Z","title":"FLAME 3 Dataset: Unleashing the Power of Radiometric Thermal UAV Imagery for Wildfire Management","version":2},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-11T23:07:00.700475Z"},"links":{"citing_paper":"/paper/2412.02831"},"observation_digest":"sha256:3d7313eb44f88ee323222a2ad0ea8ff03cd53245dfa2d01c1290efa186dbe0ea","observation_id":"5dd71137-d62d-4da5-8b7b-a61d374c2d0f","resolution":{"observed_at":"2026-08-11T23:07:01.088571Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-11T23:07:01.078172Z","title":"Attention-guided synthetic data augmentation for drone-based wildfire detection,","venue":null,"work_id":"76c8cde8-d8a7-4a4e-b550-0f8b4673d613","year":2023},"citing_paper":{"arxiv_id":"2412.02831","last_updated":"2026-06-28T17:16:26Z","snapshot_observed_at":"2026-08-14T04:47:19.489944Z","submitted_at":"2024-12-03T20:53:42Z","title":"FLAME 3 Dataset: Unleashing the Power of Radiometric Thermal UAV Imagery for Wildfire Management","version":2},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-11T23:07:00.702987Z"},"links":{"citing_paper":"/paper/2412.02831"},"observation_digest":"sha256:f08d81746fd0eb4d645e1e5676b7914bfc2ec8fd63d77f6a76fc4588290a3e0d","observation_id":"5d1cef55-f274-4318-b817-301eb5f9b384","resolution":{"observed_at":"2026-08-11T23:07:01.080862Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2403.03463","last_updated":"2024-09-30T20:23:12Z","snapshot_observed_at":"2026-08-16T14:12:26.221802Z","submitted_at":"2024-03-06T04:59:38Z","title":"FLAME Diffuser: Wildfire Image Synthesis using Mask Guided Diffusion","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2403.03463","snapshot_observed_at":"2026-08-11T23:07:00.705462Z","title":"FLAME diffuser: Grounded wildfire image synthesis using mask guided diffusion,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2412.02831","last_updated":"2026-06-28T17:16:26Z","snapshot_observed_at":"2026-08-14T04:47:19.489944Z","submitted_at":"2024-12-03T20:53:42Z","title":"FLAME 3 Dataset: Unleashing the Power of Radiometric Thermal UAV Imagery for Wildfire Management","version":2},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-11T23:07:00.705462Z"},"links":{"cited_paper":"/paper/2403.03463","citing_paper":"/paper/2412.02831"},"observation_digest":"sha256:76f5f0d0e1203be64d0bf0e02902131cbc27ac3821183051955ed91a04c2550c","observation_id":"59e0ba5f-45d0-4a82-8f27-2440ef8fe404","resolution":{"observed_at":"2026-08-11T23:07:00.705462Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2103.00020","last_updated":"2021-02-26T19:04:58Z","snapshot_observed_at":"2026-07-06T10:45:03.059688Z","submitted_at":"2021-02-26T19:04:58Z","title":"Learning Transferable Visual Models From Natural Language Supervision","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2103.00020","snapshot_observed_at":"2026-08-11T23:07:00.708411Z","title":"Learning transferable visual models from natural language supervision,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2412.02831","last_updated":"2026-06-28T17:16:26Z","snapshot_observed_at":"2026-08-14T04:47:19.489944Z","submitted_at":"2024-12-03T20:53:42Z","title":"FLAME 3 Dataset: Unleashing the Power of Radiometric Thermal UAV Imagery for Wildfire Management","version":2},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-11T23:07:00.708411Z"},"links":{"cited_paper":"/paper/2103.00020","citing_paper":"/paper/2412.02831"},"observation_digest":"sha256:39c567ea2ab983e36ea5435b1c6c476df3c8ed0da4a2c1e8a91a5a9403dd8a62","observation_id":"c8b5c12f-77c3-4c82-bc9d-49ea7c2d1bca","resolution":{"observed_at":"2026-08-11T23:07:00.708411Z","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":"2026-08-11T23:07:01.071333Z","title":"Thermal image calibration and correction using unpaired cycle-consistent adversarial networks,","venue":null,"work_id":"f5a83a96-4712-42b0-b529-f3f437a498bc","year":2023},"citing_paper":{"arxiv_id":"2412.02831","last_updated":"2026-06-28T17:16:26Z","snapshot_observed_at":"2026-08-14T04:47:19.489944Z","submitted_at":"2024-12-03T20:53:42Z","title":"FLAME 3 Dataset: Unleashing the Power of Radiometric Thermal UAV Imagery for Wildfire Management","version":2},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-11T23:07:00.710746Z"},"links":{"citing_paper":"/paper/2412.02831"},"observation_digest":"sha256:b243bbad85f6328fd7c498686add7513b432f58704e04fba524a30e7c8490413","observation_id":"e72afc06-698a-4b89-9b4b-f52215ab766f","resolution":{"observed_at":"2026-08-11T23:07:01.074052Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1703.10593","last_updated":"2020-08-24T16:51:03Z","snapshot_observed_at":"2026-08-18T06:11:58.084027Z","submitted_at":"2017-03-30T17:44:17Z","title":"Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks","version":7},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1703.10593","snapshot_observed_at":"2026-08-11T23:07:00.712809Z","title":"Unpaired image-to-image translation using cycle-consistent adversarial networks,","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2412.02831","last_updated":"2026-06-28T17:16:26Z","snapshot_observed_at":"2026-08-14T04:47:19.489944Z","submitted_at":"2024-12-03T20:53:42Z","title":"FLAME 3 Dataset: Unleashing the Power of Radiometric Thermal UAV Imagery for Wildfire Management","version":2},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-11T23:07:00.712809Z"},"links":{"cited_paper":"/paper/1703.10593","citing_paper":"/paper/2412.02831"},"observation_digest":"sha256:3b758f233fdfd22ef632dd7b045145594f96b1dfe8eb1bb79b1f6fce2fe80fcd","observation_id":"ea6a8b1f-10e9-4200-b5f5-febdd47e5db1","resolution":{"observed_at":"2026-08-11T23:07:00.712809Z","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":"2026-08-11T23:07:01.064378Z","title":"Flamefinder: Illuminat- ing obscured fire through smoke with attentive deep metric learning,","venue":null,"work_id":"c15c1e47-7fda-4270-ade7-a876553067ce","year":2024},"citing_paper":{"arxiv_id":"2412.02831","last_updated":"2026-06-28T17:16:26Z","snapshot_observed_at":"2026-08-14T04:47:19.489944Z","submitted_at":"2024-12-03T20:53:42Z","title":"FLAME 3 Dataset: Unleashing the Power of Radiometric Thermal UAV Imagery for Wildfire Management","version":2},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-11T23:07:00.715312Z"},"links":{"citing_paper":"/paper/2412.02831"},"observation_digest":"sha256:48741657e6dc4f4bf4b7bc5473f9316d1bd375641e287690a7f0f6880a016449","observation_id":"622cc96a-92ab-48db-a513-db2675fc2359","resolution":{"observed_at":"2026-08-11T23:07:01.067216Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-11T23:07:01.057367Z","title":"Hardware acceleration for real-time wildfire detection onboard drone networks,","venue":null,"work_id":"83e0e57c-9043-4788-907f-904bf703be9c","year":2024},"citing_paper":{"arxiv_id":"2412.02831","last_updated":"2026-06-28T17:16:26Z","snapshot_observed_at":"2026-08-14T04:47:19.489944Z","submitted_at":"2024-12-03T20:53:42Z","title":"FLAME 3 Dataset: Unleashing the Power of Radiometric Thermal UAV Imagery for Wildfire Management","version":2},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-11T23:07:00.717387Z"},"links":{"citing_paper":"/paper/2412.02831"},"observation_digest":"sha256:0570b75c95f94279d7ff8fd8ef9cf6464c3baefa3c3b1a527bf004d54616e09d","observation_id":"aa0e3255-4398-4f11-9445-70383794ec49","resolution":{"observed_at":"2026-08-11T23:07:01.060084Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-11T23:07:01.051253Z","title":"Land and atmosphere precursors to fuel loading, wildfire ignition and post-fire recovery,","venue":null,"work_id":"bffdb281-ea7c-4ec3-af16-5d7cfa760085","year":2024},"citing_paper":{"arxiv_id":"2412.02831","last_updated":"2026-06-28T17:16:26Z","snapshot_observed_at":"2026-08-14T04:47:19.489944Z","submitted_at":"2024-12-03T20:53:42Z","title":"FLAME 3 Dataset: Unleashing the Power of Radiometric Thermal UAV Imagery for Wildfire Management","version":2},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-11T23:07:00.719686Z"},"links":{"citing_paper":"/paper/2412.02831"},"observation_digest":"sha256:53928aaa4debd781785da86b184bab514eff13405e355057e1beff6fbaf5562c","observation_id":"3ed77c7c-9c5b-4bf5-811c-818b27a2e956","resolution":{"observed_at":"2026-08-11T23:07:01.053644Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-11T23:07:01.044551Z","title":"Temporal and spatial monitoring of post-fire forest dynamics using time-series modis data,","venue":null,"work_id":"c395542a-0ab9-4d3f-8778-d3bb00764506","year":2014},"citing_paper":{"arxiv_id":"2412.02831","last_updated":"2026-06-28T17:16:26Z","snapshot_observed_at":"2026-08-14T04:47:19.489944Z","submitted_at":"2024-12-03T20:53:42Z","title":"FLAME 3 Dataset: Unleashing the Power of Radiometric Thermal UAV Imagery for Wildfire Management","version":2},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-11T23:07:00.724542Z"},"links":{"citing_paper":"/paper/2412.02831"},"observation_digest":"sha256:aa72609000a3753aec74ada6a7cb261589407af0bec2b80f7356614519509412","observation_id":"38010265-ceb5-462f-8bb4-192175437b99","resolution":{"observed_at":"2026-08-11T23:07:01.047272Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-11T23:07:01.038083Z","title":"Multilabel image classification with deep transfer learning for decision support on wildfire response,","venue":null,"work_id":"b45e7c0f-94e7-4308-a2c4-3160dd9fbe68","year":2021},"citing_paper":{"arxiv_id":"2412.02831","last_updated":"2026-06-28T17:16:26Z","snapshot_observed_at":"2026-08-14T04:47:19.489944Z","submitted_at":"2024-12-03T20:53:42Z","title":"FLAME 3 Dataset: Unleashing the Power of Radiometric Thermal UAV Imagery for Wildfire Management","version":2},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-08-11T23:07:00.727304Z"},"links":{"citing_paper":"/paper/2412.02831"},"observation_digest":"sha256:031983685de8abe866b8955e2231ba02ac22e5312f8c1656447f63b74af32b50","observation_id":"246a8b3c-4b62-49ed-97d3-48e276e169b3","resolution":{"observed_at":"2026-08-11T23:07:01.040682Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-11T23:07:00.729885Z","title":"Hcp: A flexible cnn framework for multi-label image classification,","venue":null,"work_id":null,"year":1901},"citing_paper":{"arxiv_id":"2412.02831","last_updated":"2026-06-28T17:16:26Z","snapshot_observed_at":"2026-08-14T04:47:19.489944Z","submitted_at":"2024-12-03T20:53:42Z","title":"FLAME 3 Dataset: Unleashing the Power of Radiometric Thermal UAV Imagery for Wildfire Management","version":2},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-08-11T23:07:00.729885Z"},"links":{"citing_paper":"/paper/2412.02831"},"observation_digest":"sha256:0fd6ffb59fb6226672cc17ced722d340a23a551c46f34b4d2ab415dbdb232062","observation_id":"ca6be337-addf-4bd7-bb14-034569873944","resolution":{"observed_at":"2026-08-11T23:07:00.729885Z","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":"2026-08-11T23:07:01.031083Z","title":null,"venue":null,"work_id":"bee30fef-0528-4be9-8cd5-6c7e5ac0a2df","year":2021},"citing_paper":{"arxiv_id":"2412.02831","last_updated":"2026-06-28T17:16:26Z","snapshot_observed_at":"2026-08-14T04:47:19.489944Z","submitted_at":"2024-12-03T20:53:42Z","title":"FLAME 3 Dataset: Unleashing the Power of Radiometric Thermal UAV Imagery for Wildfire Management","version":2},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-08-11T23:07:00.732443Z"},"links":{"citing_paper":"/paper/2412.02831"},"observation_digest":"sha256:800193dd9df7a6619f82c787d4ae9b95d2bbffd29c4b6cae3b255d657c738529","observation_id":"ba29a85f-7ff4-44b3-ae7a-7880554cc0c4","resolution":{"observed_at":"2026-08-11T23:07:01.033631Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-11T23:07:01.023690Z","title":"Visible-thermal image object detection via the combination of illumination conditions and temperature infor- mation,","venue":null,"work_id":"c3352db3-8048-4b7e-bcea-683f1c1269a0","year":2021},"citing_paper":{"arxiv_id":"2412.02831","last_updated":"2026-06-28T17:16:26Z","snapshot_observed_at":"2026-08-14T04:47:19.489944Z","submitted_at":"2024-12-03T20:53:42Z","title":"FLAME 3 Dataset: Unleashing the Power of Radiometric Thermal UAV Imagery for Wildfire Management","version":2},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-08-11T23:07:00.735058Z"},"links":{"citing_paper":"/paper/2412.02831"},"observation_digest":"sha256:2ab8a205b17fc6ac932bbf1519586fe3ecd88b92036c3ecf4a3a04674d1f5f58","observation_id":"9fc6ce59-65bf-4da0-a8eb-86f2133aa590","resolution":{"observed_at":"2026-08-11T23:07:01.026627Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-11T23:07:01.016603Z","title":"Pixels to pyrometrics: Uas-derived infrared imagery to evaluate and monitor prescribed fire behavior and effects,","venue":null,"work_id":"bd5759d2-17df-44d1-8b9e-976daca1754a","year":2024},"citing_paper":{"arxiv_id":"2412.02831","last_updated":"2026-06-28T17:16:26Z","snapshot_observed_at":"2026-08-14T04:47:19.489944Z","submitted_at":"2024-12-03T20:53:42Z","title":"FLAME 3 Dataset: Unleashing the Power of Radiometric Thermal UAV Imagery for Wildfire Management","version":2},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-08-11T23:07:00.737539Z"},"links":{"citing_paper":"/paper/2412.02831"},"observation_digest":"sha256:5c9dfeaa7ab8be0821819829d4cafb1c71a3362228100784a8c7f8edfeb7ddf8","observation_id":"a4770164-8fa2-4bea-b7d0-2c961f06ee6a","resolution":{"observed_at":"2026-08-11T23:07:01.019332Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-11T23:07:01.009029Z","title":null,"venue":null,"work_id":"67a7dfd8-50f2-4ede-a374-51a027df58fa","year":2007},"citing_paper":{"arxiv_id":"2412.02831","last_updated":"2026-06-28T17:16:26Z","snapshot_observed_at":"2026-08-14T04:47:19.489944Z","submitted_at":"2024-12-03T20:53:42Z","title":"FLAME 3 Dataset: Unleashing the Power of Radiometric Thermal UAV Imagery for Wildfire Management","version":2},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-08-11T23:07:00.740249Z"},"links":{"citing_paper":"/paper/2412.02831"},"observation_digest":"sha256:6d11a68a4411a3ed39535bfa9aa0d934ae7f918fa01bb63cc9baac636bc14dda","observation_id":"650abf3a-93ce-410b-b4e0-701387610bf4","resolution":{"observed_at":"2026-08-11T23:07:01.011881Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-11T23:07:01.001836Z","title":"Metashape professional,","venue":null,"work_id":"efeacedd-97a7-4bdd-b50e-4b8864bcc071","year":2023},"citing_paper":{"arxiv_id":"2412.02831","last_updated":"2026-06-28T17:16:26Z","snapshot_observed_at":"2026-08-14T04:47:19.489944Z","submitted_at":"2024-12-03T20:53:42Z","title":"FLAME 3 Dataset: Unleashing the Power of Radiometric Thermal UAV Imagery for Wildfire Management","version":2},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-08-11T23:07:00.742654Z"},"links":{"citing_paper":"/paper/2412.02831"},"observation_digest":"sha256:80354f082819e9bef0cbb64ad16375c266f55155fa2c2be2cf21ba5adfc82533","observation_id":"81715071-ce4c-469c-a024-3c4a6c506f8c","resolution":{"observed_at":"2026-08-11T23:07:01.004534Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-11T23:07:00.993727Z","title":"Influence of agisoft metashape parameters on uas structure from motion individual tree detection from canopy height models,","venue":null,"work_id":"8b60fb45-d6ee-4913-be91-832b98e688b7","year":2021},"citing_paper":{"arxiv_id":"2412.02831","last_updated":"2026-06-28T17:16:26Z","snapshot_observed_at":"2026-08-14T04:47:19.489944Z","submitted_at":"2024-12-03T20:53:42Z","title":"FLAME 3 Dataset: Unleashing the Power of Radiometric Thermal UAV Imagery for Wildfire Management","version":2},"reference_index":55,"source":"pdf_text","source_observed_at":"2026-08-11T23:07:00.745275Z"},"links":{"citing_paper":"/paper/2412.02831"},"observation_digest":"sha256:1e7f827f737a1f99a492d17b0858cf4672e3a871827b1148f1c81ae9006d4cbf","observation_id":"de771818-e910-4fce-ab68-bd6d5bb6b0d6","resolution":{"observed_at":"2026-08-11T23:07:00.997078Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-11T23:07:00.986031Z","title":"Wildland fire detection and monitoring using a drone-collected RGB/IR image dataset,","venue":null,"work_id":"d0ddd517-5860-46a3-bac2-eb724f330cd3","year":2022},"citing_paper":{"arxiv_id":"2412.02831","last_updated":"2026-06-28T17:16:26Z","snapshot_observed_at":"2026-08-14T04:47:19.489944Z","submitted_at":"2024-12-03T20:53:42Z","title":"FLAME 3 Dataset: Unleashing the Power of Radiometric Thermal UAV Imagery for Wildfire Management","version":2},"reference_index":56,"source":"pdf_text","source_observed_at":"2026-08-11T23:07:00.747597Z"},"links":{"citing_paper":"/paper/2412.02831"},"observation_digest":"sha256:bb126eb47fba48fbb70ea918bfd2f26f10c621477c3f547ad9800d75850f3493","observation_id":"6c2d804f-d35c-41e5-a8e5-92012a44dd8b","resolution":{"observed_at":"2026-08-11T23:07:00.988999Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1029/2023gl105324","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:07:00.765968Z","title":"Available: https://doi.org/10.1029/2023GL105324","venue":null,"work_id":"690e9122-ee0e-45e5-92b6-c5cfddada90f","year":null},"citing_paper":{"arxiv_id":"2412.02831","last_updated":"2026-06-28T17:16:26Z","snapshot_observed_at":"2026-08-14T04:47:19.489944Z","submitted_at":"2024-12-03T20:53:42Z","title":"FLAME 3 Dataset: Unleashing the Power of Radiometric Thermal UAV Imagery for Wildfire Management","version":2},"reference_index":2024,"source":"pdf_text","source_observed_at":"2026-08-11T23:07:00.721835Z"},"links":{"citing_paper":"/paper/2412.02831"},"observation_digest":"sha256:ea1565df8e2328c0260ab9b21b0fb5256482251b11a5a065a2989b13a8d1741c","observation_id":"dcf901ab-2641-46cc-9992-004bf36b15cf","resolution":{"observed_at":"2026-08-11T23:07:00.769752Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2412.02831","last_updated":"2026-06-28T17:16:26Z","latest_version":2,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-14T04:47:19.489944Z","submitted_at":"2024-12-03T20:53:42Z","title":"FLAME 3 Dataset: Unleashing the Power of Radiometric Thermal UAV Imagery for Wildfire Management"},"reference_resolution":{"displayed":56,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":7,"verified_exact":7,"verified_fuzzy":42},"total_outbound_references":56},"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":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"thesis":"As of 18 August 2026, this Paper Citation Record lists 56 of 56 outbound references and 3 inbound Pith citation observations for arXiv:2412.02831."}