{"as_of":"2026-08-13T11:33:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:afadf8de296a89162256749e16cb0f58f90555bd4683726189ec1a219be888cc","coverage":[{"denominator":21,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":21,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-10T22:49:40.466857Z","state":"measured"},{"denominator":21,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":21,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-13T06:32:02.005865+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[],"links":{"evidence":"/evidence","html":"/paper/2501.00647/citation-record","integrity":"/paper/2501.00647/integrity","json":"/paper/2501.00647/citation-record.json","paper":"/paper/2501.00647"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T22:49:41.032865Z","title":"Classification and segmentation of covid-19 cxr and chest ct images using deep learning algorithms","venue":null,"work_id":"1cd81a8e-1b1b-4c97-9449-fe256a2ba497","year":2020},"citing_paper":{"arxiv_id":"2501.00647","last_updated":"2024-12-31T21:07:40Z","snapshot_observed_at":"2026-08-13T06:32:52.946634Z","submitted_at":"2024-12-31T21:07:40Z","title":"Lightweight G-YOLOv11: Advancing Efficient Fracture Detection in Pediatric Wrist X-rays","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-10T22:49:40.335389Z"},"links":{"citing_paper":"/paper/2501.00647"},"observation_digest":"sha256:719d6c459a2d52f94cc1fffc8e04ca15c766bcb81c690ccd6e85a7f426c8f18f","observation_id":"e88b818e-4d6c-4e51-b9d7-52f3137ca5fe","resolution":{"observed_at":"2026-08-10T22:49:41.037887Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T22:49:41.013972Z","title":"Colorization technique to improve dcnn-based ich ct image classification","venue":null,"work_id":"92a52698-c1b2-44cf-a8b0-b746d9a90074","year":2022},"citing_paper":{"arxiv_id":"2501.00647","last_updated":"2024-12-31T21:07:40Z","snapshot_observed_at":"2026-08-13T06:32:52.946634Z","submitted_at":"2024-12-31T21:07:40Z","title":"Lightweight G-YOLOv11: Advancing Efficient Fracture Detection in Pediatric Wrist X-rays","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-10T22:49:40.342579Z"},"links":{"citing_paper":"/paper/2501.00647"},"observation_digest":"sha256:1df4c1557b3b49f987807a67cd5609378eab662ea06b5e9c2a441193696f10a2","observation_id":"019b8a10-d00c-4f57-a148-11f8a447a2d0","resolution":{"observed_at":"2026-08-10T22:49:41.020228Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T22:49:40.994232Z","title":"U-net-based covid-19 ct image semantic segmentation: A transfer learning approach","venue":null,"work_id":"343e3652-0577-468b-bbf0-240d73d4055f","year":2022},"citing_paper":{"arxiv_id":"2501.00647","last_updated":"2024-12-31T21:07:40Z","snapshot_observed_at":"2026-08-13T06:32:52.946634Z","submitted_at":"2024-12-31T21:07:40Z","title":"Lightweight G-YOLOv11: Advancing Efficient Fracture Detection in Pediatric Wrist X-rays","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-10T22:49:40.348566Z"},"links":{"citing_paper":"/paper/2501.00647"},"observation_digest":"sha256:fd9b6490a92cf20bcd59025f69ddb4918e80b7255fe46ab16e11e1db8874b5b1","observation_id":"43db5990-b5f1-46b6-8986-41b2f4e8654b","resolution":{"observed_at":"2026-08-10T22:49:40.999900Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T22:49:40.973825Z","title":"Residual encoder-decoder based architecture for medical image denoising","venue":null,"work_id":"e7eb9a10-dcec-4bac-bcad-f88cd1506219","year":2024},"citing_paper":{"arxiv_id":"2501.00647","last_updated":"2024-12-31T21:07:40Z","snapshot_observed_at":"2026-08-13T06:32:52.946634Z","submitted_at":"2024-12-31T21:07:40Z","title":"Lightweight G-YOLOv11: Advancing Efficient Fracture Detection in Pediatric Wrist X-rays","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-10T22:49:40.353826Z"},"links":{"citing_paper":"/paper/2501.00647"},"observation_digest":"sha256:d773e20eda87e7b42ac5ee6920bc496d81669d4e89958d9e58c19a214fef6520","observation_id":"8d2944df-cab6-4bad-a1aa-95968156e2b4","resolution":{"observed_at":"2026-08-10T22:49:40.980524Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T22:49:40.955457Z","title":"Parallelnet: Multiple backbone network for detection tasks on thigh bone fracture","venue":null,"work_id":"ffd83d00-e6eb-4abb-b19c-91a92c2ae39c","year":2021},"citing_paper":{"arxiv_id":"2501.00647","last_updated":"2024-12-31T21:07:40Z","snapshot_observed_at":"2026-08-13T06:32:52.946634Z","submitted_at":"2024-12-31T21:07:40Z","title":"Lightweight G-YOLOv11: Advancing Efficient Fracture Detection in Pediatric Wrist X-rays","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-10T22:49:40.359751Z"},"links":{"citing_paper":"/paper/2501.00647"},"observation_digest":"sha256:efab7459eae6dcdafaeaae00e055a976c025e2b3a0fd021e2523086a221d7e91","observation_id":"886acb17-a3d6-4627-9dfe-c7652996816f","resolution":{"observed_at":"2026-08-10T22:49:40.961148Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T22:49:40.934290Z","title":"Deep learning-based localization and segmentation of wrist fractures on x-ray radiographs","venue":null,"work_id":"16e1d93c-185f-4133-9cec-121329ff095e","year":2022},"citing_paper":{"arxiv_id":"2501.00647","last_updated":"2024-12-31T21:07:40Z","snapshot_observed_at":"2026-08-13T06:32:52.946634Z","submitted_at":"2024-12-31T21:07:40Z","title":"Lightweight G-YOLOv11: Advancing Efficient Fracture Detection in Pediatric Wrist X-rays","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-10T22:49:40.364948Z"},"links":{"citing_paper":"/paper/2501.00647"},"observation_digest":"sha256:c7338521fd7f481bfbbf87aaed03520572182a9beaf43b280e7ae3724dc1efb7","observation_id":"878fb37e-f161-4eaf-88b4-46839efff1a4","resolution":{"observed_at":"2026-08-10T22:49:40.941481Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T22:49:40.900147Z","title":"Enhancing wrist abnormality detection with yolo: Analysis of state-of-the-art single-stage detection models","venue":null,"work_id":"103c7c87-292a-4df1-b892-d66c37882fe5","year":2024},"citing_paper":{"arxiv_id":"2501.00647","last_updated":"2024-12-31T21:07:40Z","snapshot_observed_at":"2026-08-13T06:32:52.946634Z","submitted_at":"2024-12-31T21:07:40Z","title":"Lightweight G-YOLOv11: Advancing Efficient Fracture Detection in Pediatric Wrist X-rays","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-10T22:49:40.370404Z"},"links":{"citing_paper":"/paper/2501.00647"},"observation_digest":"sha256:16233a9758817f368109a165a5f026fb5794271a86e2d475b912b59a69bb295d","observation_id":"13e8cc92-e7e8-4382-b533-ebeb1dae97e3","resolution":{"observed_at":"2026-08-10T22:49:40.905970Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T22:49:40.879495Z","title":"A pediatric wrist trauma x-ray dataset (grazpedwri-dx) for machine learning","venue":null,"work_id":"8031cd62-fdf9-486f-8cd7-31e174561e0e","year":2022},"citing_paper":{"arxiv_id":"2501.00647","last_updated":"2024-12-31T21:07:40Z","snapshot_observed_at":"2026-08-13T06:32:52.946634Z","submitted_at":"2024-12-31T21:07:40Z","title":"Lightweight G-YOLOv11: Advancing Efficient Fracture Detection in Pediatric Wrist X-rays","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-10T22:49:40.375322Z"},"links":{"citing_paper":"/paper/2501.00647"},"observation_digest":"sha256:223e5c871872746b6b384aa148bac2a6e5ace784a92f56851f08868e9f2447b9","observation_id":"7b9df88e-f451-4776-918f-d69777c8a5c0","resolution":{"observed_at":"2026-08-10T22:49:40.886088Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T22:49:40.860323Z","title":"Fracture detection in pediatric wrist trauma x-ray images using yolov8 algorithm","venue":null,"work_id":"bb0819c1-461f-4c31-94af-27df66787e22","year":2023},"citing_paper":{"arxiv_id":"2501.00647","last_updated":"2024-12-31T21:07:40Z","snapshot_observed_at":"2026-08-13T06:32:52.946634Z","submitted_at":"2024-12-31T21:07:40Z","title":"Lightweight G-YOLOv11: Advancing Efficient Fracture Detection in Pediatric Wrist X-rays","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-10T22:49:40.380635Z"},"links":{"citing_paper":"/paper/2501.00647"},"observation_digest":"sha256:72185c494d0be8b29cc93866898557e7e3cca2fd9ae87ed82ac6837ce9ca3677","observation_id":"89f35a50-a759-466f-bd59-5d02b1197da4","resolution":{"observed_at":"2026-08-10T22:49:40.865931Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T22:49:40.843025Z","title":"Yolov9 for fracture detection in pediatric wrist trauma x-ray images","venue":null,"work_id":"5ab2cff5-d3d7-4215-a1c9-081ef028a069","year":2024},"citing_paper":{"arxiv_id":"2501.00647","last_updated":"2024-12-31T21:07:40Z","snapshot_observed_at":"2026-08-13T06:32:52.946634Z","submitted_at":"2024-12-31T21:07:40Z","title":"Lightweight G-YOLOv11: Advancing Efficient Fracture Detection in Pediatric Wrist X-rays","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-10T22:49:40.385070Z"},"links":{"citing_paper":"/paper/2501.00647"},"observation_digest":"sha256:2a98f35e1ea94fe34cb2c3b0ced7ca95dba81e7cbe89f6c47403bf424c16bc67","observation_id":"f83f823b-52e7-47c8-abd6-d3c038b236bf","resolution":{"observed_at":"2026-08-10T22:49:40.848999Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2407.15689","last_updated":"2024-07-31T15:28:39Z","snapshot_observed_at":"2026-08-12T23:17:14.507985Z","submitted_at":"2024-07-22T14:54:51Z","title":"Pediatric Wrist Fracture Detection in X-rays via YOLOv10 Algorithm and Dual Label Assignment System","version":2},"cited_work":{"arxiv_id":"2407.15689","doi":null,"metadata_source":"pith","pith_arxiv_id":"2407.15689","snapshot_observed_at":"2026-08-10T22:49:40.732409Z","title":"Pediatric Wrist Fracture Detection in X-rays via YOLOv10 Algorithm and Dual Label Assignment System","venue":"eess.IV","work_id":"b4d01870-8b4c-4c38-ab51-da7394da2ade","year":2024},"citing_paper":{"arxiv_id":"2501.00647","last_updated":"2024-12-31T21:07:40Z","snapshot_observed_at":"2026-08-13T06:32:52.946634Z","submitted_at":"2024-12-31T21:07:40Z","title":"Lightweight G-YOLOv11: Advancing Efficient Fracture Detection in Pediatric Wrist X-rays","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-10T22:49:40.390628Z"},"links":{"cited_paper":"/paper/2407.15689","citing_paper":"/paper/2501.00647"},"observation_digest":"sha256:58b8e2036afa3608a66f92d75080cc8cb7f2710d1627d5fd6b245b846675887c","observation_id":"92da2777-e7e2-4914-a72c-5bd9f331ea48","resolution":{"observed_at":"2026-08-10T22:49:40.737422Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T22:49:40.822808Z","title":"Detection of bone fractures along with other abnormali- ties in wrist x-ray images using enhanced-yolo11","venue":null,"work_id":"f26e8702-6300-40af-a6b1-a5dd19ce4068","year":2024},"citing_paper":{"arxiv_id":"2501.00647","last_updated":"2024-12-31T21:07:40Z","snapshot_observed_at":"2026-08-13T06:32:52.946634Z","submitted_at":"2024-12-31T21:07:40Z","title":"Lightweight G-YOLOv11: Advancing Efficient Fracture Detection in Pediatric Wrist X-rays","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-10T22:49:40.396857Z"},"links":{"citing_paper":"/paper/2501.00647"},"observation_digest":"sha256:3c215628fbefaffeee438069e01fe2c089f5a6c53a31739dc98e5de8f7e74c8d","observation_id":"382d340c-0325-4633-b288-9f926b04a343","resolution":{"observed_at":"2026-08-10T22:49:40.829176Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2402.09329","doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T22:49:40.703821Z","title":"Yolov8-am: Yolov8 with attention mechanisms for pediatric wrist fracture detection","venue":null,"work_id":"d0376c42-092f-4094-9cbe-04505fd9ba67","year":2024},"citing_paper":{"arxiv_id":"2501.00647","last_updated":"2024-12-31T21:07:40Z","snapshot_observed_at":"2026-08-13T06:32:52.946634Z","submitted_at":"2024-12-31T21:07:40Z","title":"Lightweight G-YOLOv11: Advancing Efficient Fracture Detection in Pediatric Wrist X-rays","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-10T22:49:40.402269Z"},"links":{"citing_paper":"/paper/2501.00647"},"observation_digest":"sha256:ae66c5977b597812c6c11899a706e93392d19dfd73324499bdd224323f951cd1","observation_id":"a550e8f9-4cbd-4f22-a082-2f223c355f19","resolution":{"observed_at":"2026-08-10T22:49:40.713611Z","resolver_source":"raw_fallback","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2407.03163","last_updated":"2024-07-03T14:36:07Z","snapshot_observed_at":"2026-08-12T23:29:32.947161Z","submitted_at":"2024-07-03T14:36:07Z","title":"Global Context Modeling in YOLOv8 for Pediatric Wrist Fracture Detection","version":1},"cited_work":{"arxiv_id":"2407.03163","doi":null,"metadata_source":"pith","pith_arxiv_id":"2407.03163","snapshot_observed_at":"2026-08-10T22:49:40.582428Z","title":"Global Context Modeling in YOLOv8 for Pediatric Wrist Fracture Detection","venue":"cs.CV","work_id":"43c56e73-6a25-4820-ad24-32ffa85782d9","year":2024},"citing_paper":{"arxiv_id":"2501.00647","last_updated":"2024-12-31T21:07:40Z","snapshot_observed_at":"2026-08-13T06:32:52.946634Z","submitted_at":"2024-12-31T21:07:40Z","title":"Lightweight G-YOLOv11: Advancing Efficient Fracture Detection in Pediatric Wrist X-rays","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-10T22:49:40.407454Z"},"links":{"cited_paper":"/paper/2407.03163","citing_paper":"/paper/2501.00647"},"observation_digest":"sha256:b4ebcdee5901d37a65c9dd557d2feb8cb61884a9b0593ac8c5840ced083c0a8d","observation_id":"338de541-1cc4-42b5-8860-4d3ab4b0a6b4","resolution":{"observed_at":"2026-08-10T22:49:40.588331Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2411.16901","last_updated":"2024-11-25T20:10:10Z","snapshot_observed_at":"2026-08-12T12:43:20.985421Z","submitted_at":"2024-11-25T20:10:10Z","title":"Deep Convolutional Neural Networks Structured Pruning via Gravity Regularization","version":1},"cited_work":{"arxiv_id":"2411.16901","doi":null,"metadata_source":"pith","pith_arxiv_id":"2411.16901","snapshot_observed_at":"2026-08-10T22:49:40.559467Z","title":"Deep Convolutional Neural Networks Structured Pruning via Gravity Regularization","venue":"cs.CV","work_id":"cdadb17b-818b-4efa-ad4c-3f101e6ba198","year":2024},"citing_paper":{"arxiv_id":"2501.00647","last_updated":"2024-12-31T21:07:40Z","snapshot_observed_at":"2026-08-13T06:32:52.946634Z","submitted_at":"2024-12-31T21:07:40Z","title":"Lightweight G-YOLOv11: Advancing Efficient Fracture Detection in Pediatric Wrist X-rays","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-10T22:49:40.412364Z"},"links":{"cited_paper":"/paper/2411.16901","citing_paper":"/paper/2501.00647"},"observation_digest":"sha256:d9076d1498ddbaad62725ff3dcadc9d510f3f2568425cc8773fec4434d915f6d","observation_id":"7c214a17-2343-4cd4-975c-bc7c62016753","resolution":{"observed_at":"2026-08-10T22:49:40.565489Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2411.11079","last_updated":"2024-11-17T13:55:35Z","snapshot_observed_at":"2026-08-12T18:53:30.612764Z","submitted_at":"2024-11-17T13:55:35Z","title":"Electrostatic Force Regularization for Neural Structured Pruning","version":1},"cited_work":{"arxiv_id":"2411.11079","doi":null,"metadata_source":"pith","pith_arxiv_id":"2411.11079","snapshot_observed_at":"2026-08-10T22:49:40.526907Z","title":"Electrostatic Force Regularization for Neural Structured Pruning","venue":"cs.CV","work_id":"63c0b0be-8edb-4dab-90aa-2e0292a3e664","year":2024},"citing_paper":{"arxiv_id":"2501.00647","last_updated":"2024-12-31T21:07:40Z","snapshot_observed_at":"2026-08-13T06:32:52.946634Z","submitted_at":"2024-12-31T21:07:40Z","title":"Lightweight G-YOLOv11: Advancing Efficient Fracture Detection in Pediatric Wrist X-rays","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-10T22:49:40.419446Z"},"links":{"cited_paper":"/paper/2411.11079","citing_paper":"/paper/2501.00647"},"observation_digest":"sha256:9c781c9c0cc3eeaec61d6fedf14b02c56c5f344c145ba50c1c25ed8b1359e3cf","observation_id":"80a543d7-1bae-4c28-b1ba-8e3b12fa7724","resolution":{"observed_at":"2026-08-10T22:49:40.535602Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T22:49:40.428016Z","title":"Ghostnet: More features from cheap operations","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2501.00647","last_updated":"2024-12-31T21:07:40Z","snapshot_observed_at":"2026-08-13T06:32:52.946634Z","submitted_at":"2024-12-31T21:07:40Z","title":"Lightweight G-YOLOv11: Advancing Efficient Fracture Detection in Pediatric Wrist X-rays","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-10T22:49:40.428016Z"},"links":{"citing_paper":"/paper/2501.00647"},"observation_digest":"sha256:dbe2096a5310040b0d2f2c48adcf8239002c327bc4c5a08088c2bce31cbc34f3","observation_id":"952ecb3a-7c98-428d-8eb1-d11be79f23c8","resolution":{"observed_at":"2026-08-10T22:49:40.428016Z","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":"2026-08-10T22:49:40.791010Z","title":"Yolov3-based intracranial hemorrhage localization from ct images","venue":null,"work_id":"4dfe0664-97ae-4ae5-aaa1-59865ab2bb5b","year":2023},"citing_paper":{"arxiv_id":"2501.00647","last_updated":"2024-12-31T21:07:40Z","snapshot_observed_at":"2026-08-13T06:32:52.946634Z","submitted_at":"2024-12-31T21:07:40Z","title":"Lightweight G-YOLOv11: Advancing Efficient Fracture Detection in Pediatric Wrist X-rays","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-10T22:49:40.441266Z"},"links":{"citing_paper":"/paper/2501.00647"},"observation_digest":"sha256:26aa87d45874a6ee3a4afbf128e26f5396b7da2d145e63beb87f9c0dab22db1a","observation_id":"3fced5c4-ac19-4d6c-8cec-f464685a9152","resolution":{"observed_at":"2026-08-10T22:49:40.797165Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T22:49:40.772534Z","title":"Quadratic convolution-based yolov8 (q-yolov8) for localization of intracranial hemorrhage from head ct images","venue":null,"work_id":"6f18f05c-8718-4402-9cc2-255669b7f223","year":2024},"citing_paper":{"arxiv_id":"2501.00647","last_updated":"2024-12-31T21:07:40Z","snapshot_observed_at":"2026-08-13T06:32:52.946634Z","submitted_at":"2024-12-31T21:07:40Z","title":"Lightweight G-YOLOv11: Advancing Efficient Fracture Detection in Pediatric Wrist X-rays","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-10T22:49:40.455524Z"},"links":{"citing_paper":"/paper/2501.00647"},"observation_digest":"sha256:a31fcd1f5536ba88bd50d9c1b40e83b7da2e98cb78208f871154102fadc5271b","observation_id":"5484021c-267a-4902-919c-98eba77cfa3f","resolution":{"observed_at":"2026-08-10T22:49:40.778075Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2410.17725","last_updated":"2024-10-23T09:55:22Z","snapshot_observed_at":"2026-08-13T01:57:27.555320Z","submitted_at":"2024-10-23T09:55:22Z","title":"YOLOv11: An Overview of the Key Architectural Enhancements","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.17725","snapshot_observed_at":"2026-08-10T22:49:40.460377Z","title":"Yolov11: An overview of the key architectural enhancements","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2501.00647","last_updated":"2024-12-31T21:07:40Z","snapshot_observed_at":"2026-08-13T06:32:52.946634Z","submitted_at":"2024-12-31T21:07:40Z","title":"Lightweight G-YOLOv11: Advancing Efficient Fracture Detection in Pediatric Wrist X-rays","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-10T22:49:40.460377Z"},"links":{"cited_paper":"/paper/2410.17725","citing_paper":"/paper/2501.00647"},"observation_digest":"sha256:272d7907efc7e42d65a0c1f6dedd6eb19e6912201917a8b2ad49deefaa938a08","observation_id":"ba11382b-7dc9-4d85-a494-187262a9d4b3","resolution":{"observed_at":"2026-08-10T22:49:40.460377Z","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":"2026-08-10T22:49:40.751809Z","title":"Ultralytics yolo11, 2024","venue":null,"work_id":"c9dcb842-d6bf-49a7-9e72-010d368b3a59","year":2024},"citing_paper":{"arxiv_id":"2501.00647","last_updated":"2024-12-31T21:07:40Z","snapshot_observed_at":"2026-08-13T06:32:52.946634Z","submitted_at":"2024-12-31T21:07:40Z","title":"Lightweight G-YOLOv11: Advancing Efficient Fracture Detection in Pediatric Wrist X-rays","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-10T22:49:40.466857Z"},"links":{"citing_paper":"/paper/2501.00647"},"observation_digest":"sha256:a220317617883078dea28aec7e5db5977a734bc36a15fffda9ff9b4f04278d2f","observation_id":"73e3f7d9-de39-4158-bccd-69d375daa76c","resolution":{"observed_at":"2026-08-10T22:49:40.757747Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2501.00647","last_updated":"2024-12-31T21:07:40Z","latest_version":1,"primary_category":"eess.IV","snapshot_observed_at":"2026-08-13T06:32:52.946634Z","submitted_at":"2024-12-31T21:07:40Z","title":"Lightweight G-YOLOv11: Advancing Efficient Fracture Detection in Pediatric Wrist X-rays"},"reference_resolution":{"displayed":21,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":2,"verified_exact":5,"verified_fuzzy":14},"total_outbound_references":21},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"thesis":"As of 13 August 2026, this Paper Citation Record lists 21 of 21 outbound references and 0 inbound Pith citation observations for arXiv:2501.00647."}