{"as_of":"2026-08-19T16:45:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:56468b97493f95831965ad4edc118daefea6193f5af59d4fbb5c28bdefac2600","coverage":[{"denominator":96,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":96,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-12T14:53:01.685095Z","state":"measured"},{"denominator":97,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":97,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-19T06:32:44.657259+00:00","state":"measured"},{"denominator":1,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":1,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-06T15:00:56.379639Z","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":"2026-08-06T15:00:56.475313Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2411.14833","last_updated":"2026-07-03T07:34:00Z","snapshot_observed_at":"2026-08-18T10:54:44.358510Z","submitted_at":"2024-11-22T10:16:35Z","title":"Cell as Point: One-Stage Framework for Efficient Cell Tracking","version":4},"cited_work":{"arxiv_id":"2411.14833","doi":null,"metadata_source":"pith","pith_arxiv_id":"2411.14833","snapshot_observed_at":"2026-08-06T15:00:56.475313Z","title":"Cell as Point: One-Stage Framework for Efficient Cell Tracking","venue":"eess.IV","work_id":"9af1d5c2-158c-4e9a-85e5-ebc5798e4abc","year":2024},"citing_paper":{"arxiv_id":"2507.17149","last_updated":"2025-07-23T02:28:43Z","snapshot_observed_at":"2026-08-15T02:19:20.874585Z","submitted_at":"2025-07-23T02:28:43Z","title":"ScSAM: Debiasing Morphology and Distributional Variability in Subcellular Semantic Segmentation","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-06T15:00:56.379639Z"},"links":{"cited_paper":"/paper/2411.14833","citing_paper":"/paper/2507.17149"},"observation_digest":"sha256:fccfea6dee6d5a3b958632e96dceb924875e6c1172c299980332258034561c5f","observation_id":"33c95af0-0a53-4754-a6f8-9d2ed2476655","resolution":{"observed_at":"2026-08-06T15:00:56.481106Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2411.14833/citation-record","integrity":"/paper/2411.14833/integrity","json":"/paper/2411.14833/citation-record.json","paper":"/paper/2411.14833"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T14:53:01.318301Z","title":"Multi-class cell de- tection using spatial context representation","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2411.14833","last_updated":"2026-07-03T07:34:00Z","snapshot_observed_at":"2026-08-18T10:54:44.358510Z","submitted_at":"2024-11-22T10:16:35Z","title":"Cell as Point: One-Stage Framework for Efficient Cell Tracking","version":4},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-12T14:53:01.318301Z"},"links":{"citing_paper":"/paper/2411.14833"},"observation_digest":"sha256:b28e3c05128314cdf813e8b12cf19179917239492d5e439255c5b808542993fe","observation_id":"65cd30a7-07ca-4500-8a2f-7ce52ee0c1b4","resolution":{"observed_at":"2026-08-12T14:53:01.318301Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T14:53:01.323610Z","title":"Joint cell segmentation and tracking using cell proposals","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2411.14833","last_updated":"2026-07-03T07:34:00Z","snapshot_observed_at":"2026-08-18T10:54:44.358510Z","submitted_at":"2024-11-22T10:16:35Z","title":"Cell as Point: One-Stage Framework for Efficient Cell Tracking","version":4},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-12T14:53:01.323610Z"},"links":{"citing_paper":"/paper/2411.14833"},"observation_digest":"sha256:7ca222da8a5cb7bd2f72152f1f83b18417671b6fab4c95e6bc8a4219fda364b1","observation_id":"1036c470-cc5d-4d7e-9ff6-eb492d4b5b6a","resolution":{"observed_at":"2026-08-12T14:53:01.323610Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1705.03386","last_updated":"2017-05-09T15:30:39Z","snapshot_observed_at":"2026-08-18T10:55:29.972082Z","submitted_at":"2017-05-09T15:30:39Z","title":"Cell Tracking via Proposal Generation and Selection","version":1},"cited_work":{"arxiv_id":"1705.03386","doi":null,"metadata_source":"pith","pith_arxiv_id":"1705.03386","snapshot_observed_at":"2026-08-12T14:53:01.747040Z","title":"Cell Tracking via Proposal Generation and Selection","venue":"cs.CV","work_id":"5ed56725-f063-41d5-bb10-0d7f613b2844","year":2017},"citing_paper":{"arxiv_id":"2411.14833","last_updated":"2026-07-03T07:34:00Z","snapshot_observed_at":"2026-08-18T10:54:44.358510Z","submitted_at":"2024-11-22T10:16:35Z","title":"Cell as Point: One-Stage Framework for Efficient Cell Tracking","version":4},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-12T14:53:01.329058Z"},"links":{"cited_paper":"/paper/1705.03386","citing_paper":"/paper/2411.14833"},"observation_digest":"sha256:6684cba5e4ab23162c1e93f15c82038d302f54698f1b3719e74e408f19a8a1f4","observation_id":"f94e5f6d-c98b-417d-a9c9-bdaf882f6824","resolution":{"observed_at":"2026-08-12T14:53:01.753507Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-12T14:53:01.333409Z","title":null,"venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2411.14833","last_updated":"2026-07-03T07:34:00Z","snapshot_observed_at":"2026-08-18T10:54:44.358510Z","submitted_at":"2024-11-22T10:16:35Z","title":"Cell as Point: One-Stage Framework for Efficient Cell Tracking","version":4},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-12T14:53:01.333409Z"},"links":{"citing_paper":"/paper/2411.14833"},"observation_digest":"sha256:ee735755618902bd933927d19469a05d03b05d8ce47c4478406f9cc63a28084c","observation_id":"7094a668-c6c1-4ecd-8d2c-e73a691714e9","resolution":{"observed_at":"2026-08-12T14:53:01.333409Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T14:53:01.337455Z","title":"A probabilistic approach to joint cell tracking and segmentation in high-throughput microscopy videos.Medical image analysis, pages 140–152, 2018","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2411.14833","last_updated":"2026-07-03T07:34:00Z","snapshot_observed_at":"2026-08-18T10:54:44.358510Z","submitted_at":"2024-11-22T10:16:35Z","title":"Cell as Point: One-Stage Framework for Efficient Cell Tracking","version":4},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-12T14:53:01.337455Z"},"links":{"citing_paper":"/paper/2411.14833"},"observation_digest":"sha256:30a869f9507c2f4933430f093fdd65cfc41279528fa1405b00d675e31178dac1","observation_id":"252c3ddf-48db-4fc6-a3ce-62dc6db18339","resolution":{"observed_at":"2026-08-12T14:53:01.337455Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2106.13195","last_updated":"2021-06-24T17:20:21Z","snapshot_observed_at":"2026-08-18T18:02:38.906795Z","submitted_at":"2021-06-24T17:20:21Z","title":"FitVid: Overfitting in Pixel-Level Video Prediction","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2106.13195","snapshot_observed_at":"2026-08-12T14:53:01.341460Z","title":"Fitvid: Overfitting in pixel-level video prediction.arXiv preprint arXiv:2106.13195, 2020","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2411.14833","last_updated":"2026-07-03T07:34:00Z","snapshot_observed_at":"2026-08-18T10:54:44.358510Z","submitted_at":"2024-11-22T10:16:35Z","title":"Cell as Point: One-Stage Framework for Efficient Cell Tracking","version":4},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-12T14:53:01.341460Z"},"links":{"cited_paper":"/paper/2106.13195","citing_paper":"/paper/2411.14833"},"observation_digest":"sha256:71020ef00b1172fb1dceb298a3b65827d04b7ab2741789aeb9831e30639f19a1","observation_id":"b7e0497a-368c-4635-ba60-af7f4c7e5131","resolution":{"observed_at":"2026-08-12T14:53:01.341460Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T14:53:01.345944Z","title":"Dmnet: Dual-stream marker guided deep network for dense cell segmentation and lineage tracking","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2411.14833","last_updated":"2026-07-03T07:34:00Z","snapshot_observed_at":"2026-08-18T10:54:44.358510Z","submitted_at":"2024-11-22T10:16:35Z","title":"Cell as Point: One-Stage Framework for Efficient Cell Tracking","version":4},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-12T14:53:01.345944Z"},"links":{"citing_paper":"/paper/2411.14833"},"observation_digest":"sha256:14f6f1dbb5099031d0d139ad86ed3f1b3a530f535591fe1bd69994346b559a65","observation_id":"9b231afe-68e4-47c8-b4de-83f744495180","resolution":{"observed_at":"2026-08-12T14:53:01.345944Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T14:53:01.349588Z","title":"Graph neural net- work for cell tracking in microscopy videos","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2411.14833","last_updated":"2026-07-03T07:34:00Z","snapshot_observed_at":"2026-08-18T10:54:44.358510Z","submitted_at":"2024-11-22T10:16:35Z","title":"Cell as Point: One-Stage Framework for Efficient Cell Tracking","version":4},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-12T14:53:01.349588Z"},"links":{"citing_paper":"/paper/2411.14833"},"observation_digest":"sha256:db91f716ae80275b892f7641da3aff05ea77101fb2dbf662cbfff94b867e286f","observation_id":"4b40c88a-3ee3-44d5-8ad7-84299d6dab76","resolution":{"observed_at":"2026-08-12T14:53:01.349588Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T14:53:01.356782Z","title":"Cell segmentation and tracking in phase contrast images using graph cut with asymmetric boundary costs","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2411.14833","last_updated":"2026-07-03T07:34:00Z","snapshot_observed_at":"2026-08-18T10:54:44.358510Z","submitted_at":"2024-11-22T10:16:35Z","title":"Cell as Point: One-Stage Framework for Efficient Cell Tracking","version":4},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-12T14:53:01.356782Z"},"links":{"citing_paper":"/paper/2411.14833"},"observation_digest":"sha256:484ac44ab6689dfd52eb0eaa474299a40a7bfcfc19e93c24142c9f1c4a4bbdc0","observation_id":"bf6204bc-5772-4995-948f-f9ac4e7cfbdc","resolution":{"observed_at":"2026-08-12T14:53:01.356782Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T14:53:01.360520Z","title":"Reliable cell tracking by global data association","venue":null,"work_id":null,"year":2011},"citing_paper":{"arxiv_id":"2411.14833","last_updated":"2026-07-03T07:34:00Z","snapshot_observed_at":"2026-08-18T10:54:44.358510Z","submitted_at":"2024-11-22T10:16:35Z","title":"Cell as Point: One-Stage Framework for Efficient Cell Tracking","version":4},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-12T14:53:01.360520Z"},"links":{"citing_paper":"/paper/2411.14833"},"observation_digest":"sha256:0b4fa4f140e6d00634275eb074850ae79844f5c886d41c43da442c56b1eb6275","observation_id":"36e3db6b-386d-4eac-bcaa-2a93030c19ca","resolution":{"observed_at":"2026-08-12T14:53:01.360520Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T14:53:01.364251Z","title":"Cell tracking under high confluency conditions by candidate cell region detection-based-association ap- proach.Biomedical Engineering, pages 1004–1010, 2013","venue":null,"work_id":null,"year":2013},"citing_paper":{"arxiv_id":"2411.14833","last_updated":"2026-07-03T07:34:00Z","snapshot_observed_at":"2026-08-18T10:54:44.358510Z","submitted_at":"2024-11-22T10:16:35Z","title":"Cell as Point: One-Stage Framework for Efficient Cell Tracking","version":4},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-12T14:53:01.364251Z"},"links":{"citing_paper":"/paper/2411.14833"},"observation_digest":"sha256:43c02982fff5e471b5f7bf3fa207dbea3ccf0f6a3763b26bcd52b9fba94960a3","observation_id":"92bb61e6-0b5a-471a-9b7e-50331ed4a823","resolution":{"observed_at":"2026-08-12T14:53:01.364251Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T14:53:01.368072Z","title":"High- speed tracking-by-detection without using image informa- tion","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2411.14833","last_updated":"2026-07-03T07:34:00Z","snapshot_observed_at":"2026-08-18T10:54:44.358510Z","submitted_at":"2024-11-22T10:16:35Z","title":"Cell as Point: One-Stage Framework for Efficient Cell Tracking","version":4},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-12T14:53:01.368072Z"},"links":{"citing_paper":"/paper/2411.14833"},"observation_digest":"sha256:9b272ff06e81293dfb28904c077ca18a983b2f4e179ed78981e968e0263fa79e","observation_id":"526b88fb-ba90-4415-a3a0-5ee027d12715","resolution":{"observed_at":"2026-08-12T14:53:01.368072Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T14:53:01.371886Z","title":"Ultrack: pushing the limits of cell tracking across biological scales.bioRxiv, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2411.14833","last_updated":"2026-07-03T07:34:00Z","snapshot_observed_at":"2026-08-18T10:54:44.358510Z","submitted_at":"2024-11-22T10:16:35Z","title":"Cell as Point: One-Stage Framework for Efficient Cell Tracking","version":4},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-12T14:53:01.371886Z"},"links":{"citing_paper":"/paper/2411.14833"},"observation_digest":"sha256:675f13d7960bdf11baa02f8a680cfcb8d809ce2a75e4b98a877c5af26e712bec","observation_id":"8e5573db-adee-48e1-8394-c6829cd23973","resolution":{"observed_at":"2026-08-12T14:53:01.371886Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T14:53:01.375254Z","title":"Large- scale multi-hypotheses cell tracking using ultrametric con- tours maps","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2411.14833","last_updated":"2026-07-03T07:34:00Z","snapshot_observed_at":"2026-08-18T10:54:44.358510Z","submitted_at":"2024-11-22T10:16:35Z","title":"Cell as Point: One-Stage Framework for Efficient Cell Tracking","version":4},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-12T14:53:01.375254Z"},"links":{"citing_paper":"/paper/2411.14833"},"observation_digest":"sha256:5865f26d709bdba32be553ca894c2d42e8950971685150369389a1a95f01f96c","observation_id":"c9c81dc9-c7d6-4ad2-89c5-2a37b64df4e1","resolution":{"observed_at":"2026-08-12T14:53:01.375254Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T14:53:01.378831Z","title":"Lucas/kanade meets horn/schunck: Combining local and global optic flow methods.International Journal of Com- puter Vision, pages 211–231, 2005","venue":null,"work_id":null,"year":2005},"citing_paper":{"arxiv_id":"2411.14833","last_updated":"2026-07-03T07:34:00Z","snapshot_observed_at":"2026-08-18T10:54:44.358510Z","submitted_at":"2024-11-22T10:16:35Z","title":"Cell as Point: One-Stage Framework for Efficient Cell Tracking","version":4},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-12T14:53:01.378831Z"},"links":{"citing_paper":"/paper/2411.14833"},"observation_digest":"sha256:974f9710e7b98172e06e3987045989b3b49468b17580b8d66f10f70fb584d803","observation_id":"c03f5c85-3e97-471b-9711-248efb8b3fcc","resolution":{"observed_at":"2026-08-12T14:53:01.378831Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T14:53:01.382307Z","title":"Automated detection and tracking of cell clusters in time-lapse fluorescence microscopy im- ages.Journal of Medical and Biological Engineering, pages 18–25, 2017","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2411.14833","last_updated":"2026-07-03T07:34:00Z","snapshot_observed_at":"2026-08-18T10:54:44.358510Z","submitted_at":"2024-11-22T10:16:35Z","title":"Cell as Point: One-Stage Framework for Efficient Cell Tracking","version":4},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-12T14:53:01.382307Z"},"links":{"citing_paper":"/paper/2411.14833"},"observation_digest":"sha256:9e26df0fde04af9476eb333d28f08e1348313131e95600f101dfcb3f2f48c7bf","observation_id":"3c7ed69f-ce3d-4f1c-8a8f-00c6855e6550","resolution":{"observed_at":"2026-08-12T14:53:01.382307Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T14:53:01.385890Z","title":"Cmtt-jtracker: a fully test-time adaptive framework serving automated cell lineage construction.Briefings in Bioinformatics, 25(6): bbae591, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2411.14833","last_updated":"2026-07-03T07:34:00Z","snapshot_observed_at":"2026-08-18T10:54:44.358510Z","submitted_at":"2024-11-22T10:16:35Z","title":"Cell as Point: One-Stage Framework for Efficient Cell Tracking","version":4},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-12T14:53:01.385890Z"},"links":{"citing_paper":"/paper/2411.14833"},"observation_digest":"sha256:4c6d67c71429278dc3481e2e91214b1892345d4b016ce7e177256680501eb66e","observation_id":"e9d19596-aa21-404a-9cf3-6ef78053593f","resolution":{"observed_at":"2026-08-12T14:53:01.385890Z","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":"2026-08-12T14:53:02.595469Z","title":"Chapter 5 - cell tracking in time-lapse microscopy image sequences","venue":null,"work_id":"bed7a878-0f1a-44e4-8ffa-edc407758f90","year":2021},"citing_paper":{"arxiv_id":"2411.14833","last_updated":"2026-07-03T07:34:00Z","snapshot_observed_at":"2026-08-18T10:54:44.358510Z","submitted_at":"2024-11-22T10:16:35Z","title":"Cell as Point: One-Stage Framework for Efficient Cell Tracking","version":4},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-12T14:53:01.389475Z"},"links":{"citing_paper":"/paper/2411.14833"},"observation_digest":"sha256:c045cfe67bdc6d129f00fc876b74553041728d5af646ab7c338bb73ac8061345","observation_id":"0185a4c4-60dc-430f-afbf-089f5f79ad02","resolution":{"observed_at":"2026-08-12T14:53:02.599618Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-12T14:53:02.583126Z","title":"Cell- track r-cnn: A novel end-to-end deep neural network for cell segmentation and tracking in microscopy images","venue":null,"work_id":"cdc23e93-5914-4194-a96a-4c8c382d8948","year":2021},"citing_paper":{"arxiv_id":"2411.14833","last_updated":"2026-07-03T07:34:00Z","snapshot_observed_at":"2026-08-18T10:54:44.358510Z","submitted_at":"2024-11-22T10:16:35Z","title":"Cell as Point: One-Stage Framework for Efficient Cell Tracking","version":4},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-12T14:53:01.393204Z"},"links":{"citing_paper":"/paper/2411.14833"},"observation_digest":"sha256:2f1e4a4446ed2f3319d92c7047cc4604b1ea972377acdb64780b7e84a3eba5f9","observation_id":"348b48ab-2c55-451f-8774-d3d415235223","resolution":{"observed_at":"2026-08-12T14:53:02.587857Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-12T14:53:02.571996Z","title":"TAP-vid: A benchmark for track- ing any point in a video.Advances in Neural Information Processing Systems, pages 13610–13626, 2022","venue":null,"work_id":"6e7a5744-b8ae-436f-bb72-d1449d849329","year":2022},"citing_paper":{"arxiv_id":"2411.14833","last_updated":"2026-07-03T07:34:00Z","snapshot_observed_at":"2026-08-18T10:54:44.358510Z","submitted_at":"2024-11-22T10:16:35Z","title":"Cell as Point: One-Stage Framework for Efficient Cell Tracking","version":4},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-12T14:53:01.396787Z"},"links":{"citing_paper":"/paper/2411.14833"},"observation_digest":"sha256:9e9086c874bf847334b9b38cd4614801cef3c8c51d171773483c399ad6e47e90","observation_id":"8be04f68-b0ee-4766-84b1-1f9d42736727","resolution":{"observed_at":"2026-08-12T14:53:02.576009Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-12T14:53:02.559600Z","title":"Flownet: Learning optical flow with convolutional networks","venue":null,"work_id":"947a3d6c-51b5-448e-95d2-a782f2ec9f98","year":2015},"citing_paper":{"arxiv_id":"2411.14833","last_updated":"2026-07-03T07:34:00Z","snapshot_observed_at":"2026-08-18T10:54:44.358510Z","submitted_at":"2024-11-22T10:16:35Z","title":"Cell as Point: One-Stage Framework for Efficient Cell Tracking","version":4},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-12T14:53:01.400306Z"},"links":{"citing_paper":"/paper/2411.14833"},"observation_digest":"sha256:6c86571a1bc444d46354519c2490169f0dc4cc534736a740910004f4b400b09e","observation_id":"8abc461c-d7ae-48eb-874f-ddb02e0f84e7","resolution":{"observed_at":"2026-08-12T14:53:02.563377Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-12T14:53:02.548237Z","title":"Cell mi- gration/invasion assays and their application in cancer drug discovery.Biotechnology annual review, pages 391–421,","venue":null,"work_id":"1ff5da7a-ee0b-45d1-833c-c75076d259ad","year":null},"citing_paper":{"arxiv_id":"2411.14833","last_updated":"2026-07-03T07:34:00Z","snapshot_observed_at":"2026-08-18T10:54:44.358510Z","submitted_at":"2024-11-22T10:16:35Z","title":"Cell as Point: One-Stage Framework for Efficient Cell Tracking","version":4},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-12T14:53:01.403994Z"},"links":{"citing_paper":"/paper/2411.14833"},"observation_digest":"sha256:9641d84760366e00eca9b2244d8cde1094aef57f22fe526b113f4078396497cd","observation_id":"7e3d0a19-5e38-475b-acf3-29745a18ce29","resolution":{"observed_at":"2026-08-12T14:53:02.552549Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-12T14:53:02.537473Z","title":"Comput- erized cell tracking: Current methods, tools and challenges","venue":null,"work_id":"7ca8236b-6479-48ed-91d7-7eadba4c7e6a","year":2021},"citing_paper":{"arxiv_id":"2411.14833","last_updated":"2026-07-03T07:34:00Z","snapshot_observed_at":"2026-08-18T10:54:44.358510Z","submitted_at":"2024-11-22T10:16:35Z","title":"Cell as Point: One-Stage Framework for Efficient Cell Tracking","version":4},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-12T14:53:01.407849Z"},"links":{"citing_paper":"/paper/2411.14833"},"observation_digest":"sha256:ebea54afcb5cd27321a836ee16959af1ab543bba2c7f70ab220434480468bae3","observation_id":"b0462638-a338-4028-89d6-1ec132b4ff8e","resolution":{"observed_at":"2026-08-12T14:53:02.541229Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-12T14:53:02.526377Z","title":"Automatic fusion of segmentation and tracking labels","venue":null,"work_id":"53997c6f-71c5-4b1e-9497-aee0d36af732","year":2018},"citing_paper":{"arxiv_id":"2411.14833","last_updated":"2026-07-03T07:34:00Z","snapshot_observed_at":"2026-08-18T10:54:44.358510Z","submitted_at":"2024-11-22T10:16:35Z","title":"Cell as Point: One-Stage Framework for Efficient Cell Tracking","version":4},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-12T14:53:01.411346Z"},"links":{"citing_paper":"/paper/2411.14833"},"observation_digest":"sha256:26c6ffe8caa8a5f4a49aba96704e4cf2f5fd16d06c1d96c468560e34387afd3c","observation_id":"06edad1a-ed83-47f3-bdbf-1cc383a0b05e","resolution":{"observed_at":"2026-08-12T14:53:02.530198Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-12T14:53:02.515889Z","title":"Deepkymotracker: A tool for accurate construction of cell lineage trees for highly motile cells.PloS one, 20(2):e0315947, 2025","venue":null,"work_id":"710d3a40-f1a5-46e2-84d9-f45b47d7c1aa","year":2025},"citing_paper":{"arxiv_id":"2411.14833","last_updated":"2026-07-03T07:34:00Z","snapshot_observed_at":"2026-08-18T10:54:44.358510Z","submitted_at":"2024-11-22T10:16:35Z","title":"Cell as Point: One-Stage Framework for Efficient Cell Tracking","version":4},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-12T14:53:01.414866Z"},"links":{"citing_paper":"/paper/2411.14833"},"observation_digest":"sha256:106555c3d4cbdee310d35437392884a2eae5c7d5b8ad9eb12167bc4485d13ae1","observation_id":"65a84665-460c-4627-8240-f274ff60fdbb","resolution":{"observed_at":"2026-08-12T14:53:02.519684Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-12T14:53:02.504287Z","title":"Trackastra: Transformer-based cell tracking for live-cell microscopy","venue":null,"work_id":"a0c0d7bc-1919-4258-bf90-5e12f07fc202","year":2024},"citing_paper":{"arxiv_id":"2411.14833","last_updated":"2026-07-03T07:34:00Z","snapshot_observed_at":"2026-08-18T10:54:44.358510Z","submitted_at":"2024-11-22T10:16:35Z","title":"Cell as Point: One-Stage Framework for Efficient Cell Tracking","version":4},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-12T14:53:01.418737Z"},"links":{"citing_paper":"/paper/2411.14833"},"observation_digest":"sha256:5fe1a6bf648d8679f0605cd77ab07e54d9d5c069415338b45a964dfcc15dc106","observation_id":"cdc82893-a0ae-482b-8f91-f13a1ccb13ca","resolution":{"observed_at":"2026-08-12T14:53:02.508928Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-12T14:53:02.493117Z","title":"The light-sheet microscopy revolution.Journal of Optics, page 053002,","venue":null,"work_id":"841d58fb-b46e-4aad-8a2b-cfb44a5792cd","year":null},"citing_paper":{"arxiv_id":"2411.14833","last_updated":"2026-07-03T07:34:00Z","snapshot_observed_at":"2026-08-18T10:54:44.358510Z","submitted_at":"2024-11-22T10:16:35Z","title":"Cell as Point: One-Stage Framework for Efficient Cell Tracking","version":4},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-12T14:53:01.422939Z"},"links":{"citing_paper":"/paper/2411.14833"},"observation_digest":"sha256:4a901702a257442aa01185bb020006f57b8f4bd40a8464dbcbaba7fe9cb812cf","observation_id":"fb28b513-c109-4cfe-b86c-75f8a80b3b49","resolution":{"observed_at":"2026-08-12T14:53:02.497172Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-12T14:53:02.482449Z","title":"Celltrackscolab is a plat- form that enables compilation, analysis, and exploration of cell tracking data.Plos Biology, 22(8):e3002740, 2024","venue":null,"work_id":"7b74908c-c037-4f3f-9a0b-b4ebb44dab57","year":2024},"citing_paper":{"arxiv_id":"2411.14833","last_updated":"2026-07-03T07:34:00Z","snapshot_observed_at":"2026-08-18T10:54:44.358510Z","submitted_at":"2024-11-22T10:16:35Z","title":"Cell as Point: One-Stage Framework for Efficient Cell Tracking","version":4},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-12T14:53:01.426645Z"},"links":{"citing_paper":"/paper/2411.14833"},"observation_digest":"sha256:1265afca4bf7160ffb6c1331c21deb9800bb7ad967c017fc983f5f462b9f9f77","observation_id":"1e910d84-ad73-4574-917d-8548000a0684","resolution":{"observed_at":"2026-08-12T14:53:02.486171Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-12T14:53:02.472222Z","title":"Particle video revisited: Tracking through occlusions using point trajectories","venue":null,"work_id":"627d12ca-abaf-4250-ad93-9c81a9b6080b","year":2022},"citing_paper":{"arxiv_id":"2411.14833","last_updated":"2026-07-03T07:34:00Z","snapshot_observed_at":"2026-08-18T10:54:44.358510Z","submitted_at":"2024-11-22T10:16:35Z","title":"Cell as Point: One-Stage Framework for Efficient Cell Tracking","version":4},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-12T14:53:01.430145Z"},"links":{"citing_paper":"/paper/2411.14833"},"observation_digest":"sha256:5c31fcd2693a8dfd07fdeb8176115892f1e80c2a8209bb9f4233970b0e760c78","observation_id":"8ecb872e-4d53-4838-8623-73be8fcbcb86","resolution":{"observed_at":"2026-08-12T14:53:02.475756Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-12T14:53:02.462336Z","title":"Cell tracking with deep learning for cell detection and motion estimation in low- frame-rate","venue":null,"work_id":"98b7f0d5-0c30-49e4-a61a-1a79841666d4","year":2019},"citing_paper":{"arxiv_id":"2411.14833","last_updated":"2026-07-03T07:34:00Z","snapshot_observed_at":"2026-08-18T10:54:44.358510Z","submitted_at":"2024-11-22T10:16:35Z","title":"Cell as Point: One-Stage Framework for Efficient Cell Tracking","version":4},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-12T14:53:01.433797Z"},"links":{"citing_paper":"/paper/2411.14833"},"observation_digest":"sha256:5911aa5d3caf65624131b1e1a8aeba65dac9592cd105b72c9c81b4aa685db667","observation_id":"7d20cbdb-6192-4bfa-8823-39a3c9077bcc","resolution":{"observed_at":"2026-08-12T14:53:02.465831Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-12T14:53:02.452138Z","title":"Mpm: Joint representation of motion and position map for cell tracking","venue":null,"work_id":"08d182c1-d28b-4260-9792-603e07d62434","year":2020},"citing_paper":{"arxiv_id":"2411.14833","last_updated":"2026-07-03T07:34:00Z","snapshot_observed_at":"2026-08-18T10:54:44.358510Z","submitted_at":"2024-11-22T10:16:35Z","title":"Cell as Point: One-Stage Framework for Efficient Cell Tracking","version":4},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-12T14:53:01.437292Z"},"links":{"citing_paper":"/paper/2411.14833"},"observation_digest":"sha256:8151acbf19d810dfb0a6c0fb9aa472b4540ff377f1ae2b8606639366210040c7","observation_id":"5df20900-d7be-408f-ba53-2190b7040e12","resolution":{"observed_at":"2026-08-12T14:53:02.455879Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-12T14:53:02.441367Z","title":"Con- sistent cell tracking in multi-frames with spatio-temporal context by object-level warping loss","venue":null,"work_id":"c223dc0e-26de-436c-8b82-c5986281d877","year":2022},"citing_paper":{"arxiv_id":"2411.14833","last_updated":"2026-07-03T07:34:00Z","snapshot_observed_at":"2026-08-18T10:54:44.358510Z","submitted_at":"2024-11-22T10:16:35Z","title":"Cell as Point: One-Stage Framework for Efficient Cell Tracking","version":4},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-12T14:53:01.440702Z"},"links":{"citing_paper":"/paper/2411.14833"},"observation_digest":"sha256:7f2191af11336e6f65985ba036348fcbc598c42ec67c8ec2284def1b2508e9fc","observation_id":"3c4bb56b-859a-479d-b5cb-0d2d0d44d3e1","resolution":{"observed_at":"2026-08-12T14:53:02.445184Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-12T14:53:02.430797Z","title":null,"venue":null,"work_id":"48be527b-6269-4913-b1dc-51505de09fc0","year":2017},"citing_paper":{"arxiv_id":"2411.14833","last_updated":"2026-07-03T07:34:00Z","snapshot_observed_at":"2026-08-18T10:54:44.358510Z","submitted_at":"2024-11-22T10:16:35Z","title":"Cell as Point: One-Stage Framework for Efficient Cell Tracking","version":4},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-12T14:53:01.444359Z"},"links":{"citing_paper":"/paper/2411.14833"},"observation_digest":"sha256:bee823261f3fbfe96d3da57cff183ec190ec8708586ea343ae17d04c05527f69","observation_id":"717a32f0-ed97-4c61-a5dd-0f1cc531adf1","resolution":{"observed_at":"2026-08-12T14:53:02.434337Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-12T14:53:02.419930Z","title":"Visual tracking of numerous targets via multi- bernoulli filtering of image data.Pattern Recognition, pages 3625–3635, 2012","venue":null,"work_id":"dacc346a-3e98-4eeb-bd93-b68c99af1080","year":2012},"citing_paper":{"arxiv_id":"2411.14833","last_updated":"2026-07-03T07:34:00Z","snapshot_observed_at":"2026-08-18T10:54:44.358510Z","submitted_at":"2024-11-22T10:16:35Z","title":"Cell as Point: One-Stage Framework for Efficient Cell Tracking","version":4},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-12T14:53:01.448285Z"},"links":{"citing_paper":"/paper/2411.14833"},"observation_digest":"sha256:d270f21b265e832547fbb6a28a8a8aa3e39d4ca24c78c594873cf6f7f7a19dd4","observation_id":"097c9d47-ee23-4bd7-a8d5-517935605654","resolution":{"observed_at":"2026-08-12T14:53:02.424066Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-12T14:53:02.409728Z","title":"Visual mitosis detection and cell tracking using labeled multi-bernoulli filter","venue":null,"work_id":"c3410dde-9a85-4c1f-b651-c24f9804f483","year":2018},"citing_paper":{"arxiv_id":"2411.14833","last_updated":"2026-07-03T07:34:00Z","snapshot_observed_at":"2026-08-18T10:54:44.358510Z","submitted_at":"2024-11-22T10:16:35Z","title":"Cell as Point: One-Stage Framework for Efficient Cell Tracking","version":4},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-12T14:53:01.452221Z"},"links":{"citing_paper":"/paper/2411.14833"},"observation_digest":"sha256:3f007d55c4a03ff9e480010cbafeab9e3fe2c450ff5068db4ac5eb8b71c9291d","observation_id":"73db8bc7-9ac9-4b2d-aea7-73cdc37c1cdf","resolution":{"observed_at":"2026-08-12T14:53:02.413443Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-12T14:53:02.399575Z","title":"Flownet 2.0: Evolu- tion of optical flow estimation with deep networks","venue":null,"work_id":"540e7d27-723c-4018-8054-e29c88f09f10","year":2017},"citing_paper":{"arxiv_id":"2411.14833","last_updated":"2026-07-03T07:34:00Z","snapshot_observed_at":"2026-08-18T10:54:44.358510Z","submitted_at":"2024-11-22T10:16:35Z","title":"Cell as Point: One-Stage Framework for Efficient Cell Tracking","version":4},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-12T14:53:01.456708Z"},"links":{"citing_paper":"/paper/2411.14833"},"observation_digest":"sha256:59d8236bf0ed935bdd3daac59f0cba4d634b8f2d991aa81e12c8cb51a37b238a","observation_id":"c7f1c81c-b0a7-4b23-b81c-fbc2c8a0fa48","resolution":{"observed_at":"2026-08-12T14:53:02.403279Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-12T14:53:02.389476Z","title":"Cell division and the mitotic spindle.The Journal of cell biology, pages 131s–147s, 1981","venue":null,"work_id":"a9031447-904b-4f3d-a409-5277ea231169","year":1981},"citing_paper":{"arxiv_id":"2411.14833","last_updated":"2026-07-03T07:34:00Z","snapshot_observed_at":"2026-08-18T10:54:44.358510Z","submitted_at":"2024-11-22T10:16:35Z","title":"Cell as Point: One-Stage Framework for Efficient Cell Tracking","version":4},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-12T14:53:01.461056Z"},"links":{"citing_paper":"/paper/2411.14833"},"observation_digest":"sha256:0cdbd62e68ae5c11a289feba9841f1de12c143025b979a5d7f379dbf3794d975","observation_id":"5b875275-7553-4008-8986-938cfc556961","resolution":{"observed_at":"2026-08-12T14:53:02.393090Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-12T14:53:02.379308Z","title":"Unsupervised learning of multi-frame optical flow with occlusions","venue":null,"work_id":"d28b049a-5786-4dda-90ee-a91b76a41f60","year":2018},"citing_paper":{"arxiv_id":"2411.14833","last_updated":"2026-07-03T07:34:00Z","snapshot_observed_at":"2026-08-18T10:54:44.358510Z","submitted_at":"2024-11-22T10:16:35Z","title":"Cell as Point: One-Stage Framework for Efficient Cell Tracking","version":4},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-12T14:53:01.464510Z"},"links":{"citing_paper":"/paper/2411.14833"},"observation_digest":"sha256:edb117b15b81b27489275de6edf08a386843220e62f0be9fee98f8ad21289b1f","observation_id":"c711da12-cefd-4d93-9be5-c460b072cfc6","resolution":{"observed_at":"2026-08-12T14:53:02.382797Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-12T14:53:02.369272Z","title":"Multiple particle tracking in time-lapse synchrotron x-ray images using dis- criminative appearance and neighbouring topology learning","venue":null,"work_id":"a46a31bc-43ad-4ee9-b45a-da36d7c60258","year":2019},"citing_paper":{"arxiv_id":"2411.14833","last_updated":"2026-07-03T07:34:00Z","snapshot_observed_at":"2026-08-18T10:54:44.358510Z","submitted_at":"2024-11-22T10:16:35Z","title":"Cell as Point: One-Stage Framework for Efficient Cell Tracking","version":4},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-12T14:53:01.468209Z"},"links":{"citing_paper":"/paper/2411.14833"},"observation_digest":"sha256:a9ac5ac3c6d8bf4d24a0d82d3aa2bb6ba8e157b92ddb414993ce36192039585b","observation_id":"84f80388-fe43-4143-ac42-e2ae1de6e5d9","resolution":{"observed_at":"2026-08-12T14:53:02.372807Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-12T14:53:02.359045Z","title":"Tracking correction method for rapid and random protein molecules movement","venue":null,"work_id":"574a38de-d501-4277-8027-cf8c2bc43aae","year":2024},"citing_paper":{"arxiv_id":"2411.14833","last_updated":"2026-07-03T07:34:00Z","snapshot_observed_at":"2026-08-18T10:54:44.358510Z","submitted_at":"2024-11-22T10:16:35Z","title":"Cell as Point: One-Stage Framework for Efficient Cell Tracking","version":4},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-12T14:53:01.471851Z"},"links":{"citing_paper":"/paper/2411.14833"},"observation_digest":"sha256:4826b1a2f6d9ac196d2e39e2cbe989999671f9142662d4e27ca1ae6ab7542070","observation_id":"445b9e68-e1a5-4e8a-9007-178e4b4a7bbd","resolution":{"observed_at":"2026-08-12T14:53:02.362408Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-12T14:53:02.348901Z","title":"Measures for ranking cell trackers without manual validation.Pattern recognition, pages 2849–2859, 2013","venue":null,"work_id":"c2203db7-bb80-4dfd-adc4-996e1fe8e0de","year":2013},"citing_paper":{"arxiv_id":"2411.14833","last_updated":"2026-07-03T07:34:00Z","snapshot_observed_at":"2026-08-18T10:54:44.358510Z","submitted_at":"2024-11-22T10:16:35Z","title":"Cell as Point: One-Stage Framework for Efficient Cell Tracking","version":4},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-12T14:53:01.475374Z"},"links":{"citing_paper":"/paper/2411.14833"},"observation_digest":"sha256:9398276a9f2a1c0beab89836d80af1f0077dfe69ae67cec4314265a16f1f1812","observation_id":"537049cf-1e7a-4929-937a-9106947eabcf","resolution":{"observed_at":"2026-08-12T14:53:02.352667Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2410.11831","last_updated":"2024-10-15T17:56:32Z","snapshot_observed_at":"2026-08-18T10:54:06.071321Z","submitted_at":"2024-10-15T17:56:32Z","title":"CoTracker3: Simpler and Better Point Tracking by Pseudo-Labelling Real Videos","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.11831","snapshot_observed_at":"2026-08-12T14:53:01.479031Z","title":"Co- tracker3: Simpler and better point tracking by pseudo- labelling real videos.arXiv preprint arXiv:2410.11831,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2411.14833","last_updated":"2026-07-03T07:34:00Z","snapshot_observed_at":"2026-08-18T10:54:44.358510Z","submitted_at":"2024-11-22T10:16:35Z","title":"Cell as Point: One-Stage Framework for Efficient Cell Tracking","version":4},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-12T14:53:01.479031Z"},"links":{"cited_paper":"/paper/2410.11831","citing_paper":"/paper/2411.14833"},"observation_digest":"sha256:02abc3c1de80f7aab461c7a83f6d39e4caa6139e3657ee5a09d4d998ff52f4fc","observation_id":"8284d63d-7d05-41ad-94fe-6fd26af9d043","resolution":{"observed_at":"2026-08-12T14:53:01.479031Z","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":"2026-08-12T14:53:02.338266Z","title":"Co- Tracker: It is better to track together","venue":null,"work_id":"365970fb-8ec2-4e14-9ac5-aef337d7b256","year":2024},"citing_paper":{"arxiv_id":"2411.14833","last_updated":"2026-07-03T07:34:00Z","snapshot_observed_at":"2026-08-18T10:54:44.358510Z","submitted_at":"2024-11-22T10:16:35Z","title":"Cell as Point: One-Stage Framework for Efficient Cell Tracking","version":4},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-12T14:53:01.483889Z"},"links":{"citing_paper":"/paper/2411.14833"},"observation_digest":"sha256:d8aab4ecb955394c7a18bed5ac771057d3e29db6079e196ef89cdd07501c5bb3","observation_id":"d5ce06c5-55db-40dc-bd2f-f279ee6352cc","resolution":{"observed_at":"2026-08-12T14:53:02.342198Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-12T14:53:02.328077Z","title":"Phase contrast time-lapse microscopy datasets with auto- mated and manual cell tracking annotations.Scientific data, 5(1):1–12, 2018","venue":null,"work_id":"c2d90a98-739e-47c7-ace2-c2a915c57ba6","year":2018},"citing_paper":{"arxiv_id":"2411.14833","last_updated":"2026-07-03T07:34:00Z","snapshot_observed_at":"2026-08-18T10:54:44.358510Z","submitted_at":"2024-11-22T10:16:35Z","title":"Cell as Point: One-Stage Framework for Efficient Cell Tracking","version":4},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-12T14:53:01.487703Z"},"links":{"citing_paper":"/paper/2411.14833"},"observation_digest":"sha256:cd59a2ba6b7cfb5e6a97f6abef4c03949bee50927c4140ea4cf5a51375de18e0","observation_id":"8a87dd06-b32d-4448-8948-5f5ca898f054","resolution":{"observed_at":"2026-08-12T14:53:02.331707Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-12T14:53:02.317628Z","title":"Cell tracking-by- detection using elliptical bounding boxes.Journal of Visual Communication and Image Representation, page 104425,","venue":null,"work_id":"2a2ad330-fd7f-4a6c-8559-21dc506668cb","year":null},"citing_paper":{"arxiv_id":"2411.14833","last_updated":"2026-07-03T07:34:00Z","snapshot_observed_at":"2026-08-18T10:54:44.358510Z","submitted_at":"2024-11-22T10:16:35Z","title":"Cell as Point: One-Stage Framework for Efficient Cell Tracking","version":4},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-12T14:53:01.491635Z"},"links":{"citing_paper":"/paper/2411.14833"},"observation_digest":"sha256:4f2a91b398a58c812ab354183e7dd6ff962f4919e1fad60c8ef3d321e193eaf4","observation_id":"77442f13-efa8-4ef8-a501-81c285ff0d69","resolution":{"observed_at":"2026-08-12T14:53:02.321462Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-12T14:53:02.306815Z","title":"Learning from imbalanced data: open challenges and future directions.Progress in artificial intel- ligence, pages 221–232, 2016","venue":null,"work_id":"ecc4b339-3a5f-487c-b241-960dc6d5028b","year":2016},"citing_paper":{"arxiv_id":"2411.14833","last_updated":"2026-07-03T07:34:00Z","snapshot_observed_at":"2026-08-18T10:54:44.358510Z","submitted_at":"2024-11-22T10:16:35Z","title":"Cell as Point: One-Stage Framework for Efficient Cell Tracking","version":4},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-12T14:53:01.495702Z"},"links":{"citing_paper":"/paper/2411.14833"},"observation_digest":"sha256:d6c2230c7cfa5fd61ea1428f9fb8338d40c2307b4633e7347596fcb7b76bb643","observation_id":"8c0ff4ed-c724-4da5-afe4-04239edc4e86","resolution":{"observed_at":"2026-08-12T14:53:02.310730Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-12T14:53:02.296221Z","title":"Spatial omics and multiplexed imaging to explore cancer biology","venue":null,"work_id":"3c0549f2-4fbf-41f1-bd5a-95fc77da92af","year":2021},"citing_paper":{"arxiv_id":"2411.14833","last_updated":"2026-07-03T07:34:00Z","snapshot_observed_at":"2026-08-18T10:54:44.358510Z","submitted_at":"2024-11-22T10:16:35Z","title":"Cell as Point: One-Stage Framework for Efficient Cell Tracking","version":4},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-12T14:53:01.499722Z"},"links":{"citing_paper":"/paper/2411.14833"},"observation_digest":"sha256:05433e68a640eaf710bcaaf53d8ac375887929e56c0014a3db538b0c7245f16e","observation_id":"f8def402-3d32-4ce0-a29f-bd4c5ab59eb0","resolution":{"observed_at":"2026-08-12T14:53:02.300312Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-12T14:53:02.285144Z","title":"Cell population tracking and lineage construction with spatiotemporal context.Medical image analysis, pages 546–566, 2008","venue":null,"work_id":"ba73a5a4-a57b-4e23-98b8-65e3499a7804","year":2008},"citing_paper":{"arxiv_id":"2411.14833","last_updated":"2026-07-03T07:34:00Z","snapshot_observed_at":"2026-08-18T10:54:44.358510Z","submitted_at":"2024-11-22T10:16:35Z","title":"Cell as Point: One-Stage Framework for Efficient Cell Tracking","version":4},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-08-12T14:53:01.503629Z"},"links":{"citing_paper":"/paper/2411.14833"},"observation_digest":"sha256:5cb85069e55dc54b086c67d4b1016dd312f8116bb9f2cac065c7be6299e5a432","observation_id":"a4a886b8-5f2e-4465-91bc-f342967bb7f8","resolution":{"observed_at":"2026-08-12T14:53:02.289048Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-12T14:53:02.274327Z","title":"Towards an end-to-end framework for flow-guided video inpainting","venue":null,"work_id":"230276ff-0e86-4beb-9ddb-c44225b2c2aa","year":2022},"citing_paper":{"arxiv_id":"2411.14833","last_updated":"2026-07-03T07:34:00Z","snapshot_observed_at":"2026-08-18T10:54:44.358510Z","submitted_at":"2024-11-22T10:16:35Z","title":"Cell as Point: One-Stage Framework for Efficient Cell Tracking","version":4},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-08-12T14:53:01.507649Z"},"links":{"citing_paper":"/paper/2411.14833"},"observation_digest":"sha256:05e0c65d871638007802c9e143693212a1af959ef0a3149aa510bce10e2a205e","observation_id":"41efbcab-b2cb-4cff-b976-0cdaac8858a4","resolution":{"observed_at":"2026-08-12T14:53:02.278227Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-12T14:53:02.263870Z","title":"Mitosis detection in phase contrast microscopy image sequences of stem cell populations: A critical review.IEEE Transactions on Big Data, pages 443–457, 2017","venue":null,"work_id":"e60b0b68-b2e8-4ba3-ba54-fada89ace539","year":2017},"citing_paper":{"arxiv_id":"2411.14833","last_updated":"2026-07-03T07:34:00Z","snapshot_observed_at":"2026-08-18T10:54:44.358510Z","submitted_at":"2024-11-22T10:16:35Z","title":"Cell as Point: One-Stage Framework for Efficient Cell Tracking","version":4},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-08-12T14:53:01.511566Z"},"links":{"citing_paper":"/paper/2411.14833"},"observation_digest":"sha256:215ae00e8a0faa3e11085ce0d502215b17eeaab58d32e07228f45b225e65af92","observation_id":"5a89f5ec-7939-45a7-b8c3-3e9c6116f6bf","resolution":{"observed_at":"2026-08-12T14:53:02.267681Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-12T14:53:02.252912Z","title":"Overfitting the data: Compact neu- ral video delivery via content-aware feature modulation","venue":null,"work_id":"c80a6d11-fd7e-46f4-b55d-c4328cd31954","year":2021},"citing_paper":{"arxiv_id":"2411.14833","last_updated":"2026-07-03T07:34:00Z","snapshot_observed_at":"2026-08-18T10:54:44.358510Z","submitted_at":"2024-11-22T10:16:35Z","title":"Cell as Point: One-Stage Framework for Efficient Cell Tracking","version":4},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-08-12T14:53:01.516655Z"},"links":{"citing_paper":"/paper/2411.14833"},"observation_digest":"sha256:a4d4e07a848a69d7ab63ba2e9196be54023870140c7ddd314cf0a3938693f337","observation_id":"a01cc9c2-7e2c-49fa-bacf-83cb3226f865","resolution":{"observed_at":"2026-08-12T14:53:02.257066Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-12T14:53:02.242716Z","title":"Automatic 3d tracking system for large swarm of moving objects.Pattern Recognition, pages 384–396, 2016","venue":null,"work_id":"787e3e28-6f1e-460f-ae34-f22882afd407","year":2016},"citing_paper":{"arxiv_id":"2411.14833","last_updated":"2026-07-03T07:34:00Z","snapshot_observed_at":"2026-08-18T10:54:44.358510Z","submitted_at":"2024-11-22T10:16:35Z","title":"Cell as Point: One-Stage Framework for Efficient Cell Tracking","version":4},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-08-12T14:53:01.520914Z"},"links":{"citing_paper":"/paper/2411.14833"},"observation_digest":"sha256:c3eff32602fba65e0b70fd862d8b50d8de95f38eafe89614b4f8f783812c91a7","observation_id":"5984e37d-9a8e-4454-b009-16963e15edcc","resolution":{"observed_at":"2026-08-12T14:53:02.246285Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-12T14:53:02.231638Z","title":"A graph- based cell tracking algorithm with few manually tunable pa- rameters and automated segmentation error correction.PloS one, page e0249257, 2021","venue":null,"work_id":"dafbeba0-09f2-448f-91ff-f9b763e30a17","year":2021},"citing_paper":{"arxiv_id":"2411.14833","last_updated":"2026-07-03T07:34:00Z","snapshot_observed_at":"2026-08-18T10:54:44.358510Z","submitted_at":"2024-11-22T10:16:35Z","title":"Cell as Point: One-Stage Framework for Efficient Cell Tracking","version":4},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-08-12T14:53:01.524448Z"},"links":{"citing_paper":"/paper/2411.14833"},"observation_digest":"sha256:64d44d1a3780ba5bc9107c2e4f48b3b115c8c0eec0f89c6cffa1dac47ef20b75","observation_id":"1d1de3fe-9f2e-4be2-b69f-223d42af6e0b","resolution":{"observed_at":"2026-08-12T14:53:02.235460Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-12T14:53:02.219237Z","title":"Embed- track—simultaneous cell segmentation and tracking through learning offsets and clustering bandwidths.IEEE Access, pages 77147–77157, 2022","venue":null,"work_id":"10c9ae9f-77d8-4f1f-9ce3-db1acfbff78b","year":2022},"citing_paper":{"arxiv_id":"2411.14833","last_updated":"2026-07-03T07:34:00Z","snapshot_observed_at":"2026-08-18T10:54:44.358510Z","submitted_at":"2024-11-22T10:16:35Z","title":"Cell as Point: One-Stage Framework for Efficient Cell Tracking","version":4},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-08-12T14:53:01.528215Z"},"links":{"citing_paper":"/paper/2411.14833"},"observation_digest":"sha256:1ae4274de1a4426293203a9cb69b43a395143581c744ef35ccdafbd8b069bda2","observation_id":"42224a9d-a310-403d-aa5a-9578e2327d1e","resolution":{"observed_at":"2026-08-12T14:53:02.223034Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-12T14:53:02.208103Z","title":"Tracking of non- brownian particles using the viterbi algorithm","venue":null,"work_id":"5cbb58f6-fae0-4e51-9db1-f8d832bc0569","year":2015},"citing_paper":{"arxiv_id":"2411.14833","last_updated":"2026-07-03T07:34:00Z","snapshot_observed_at":"2026-08-18T10:54:44.358510Z","submitted_at":"2024-11-22T10:16:35Z","title":"Cell as Point: One-Stage Framework for Efficient Cell Tracking","version":4},"reference_index":55,"source":"pdf_text","source_observed_at":"2026-08-12T14:53:01.531869Z"},"links":{"citing_paper":"/paper/2411.14833"},"observation_digest":"sha256:50c4db87178d68bfc261ab1533fda475e04c34800e51edf05e12020966113725","observation_id":"53a3f30d-586f-4b30-8851-08045c6a1444","resolution":{"observed_at":"2026-08-12T14:53:02.212013Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-12T14:53:02.197272Z","title":null,"venue":null,"work_id":"5504501e-8654-47fa-a365-ff216910a2c8","year":2015},"citing_paper":{"arxiv_id":"2411.14833","last_updated":"2026-07-03T07:34:00Z","snapshot_observed_at":"2026-08-18T10:54:44.358510Z","submitted_at":"2024-11-22T10:16:35Z","title":"Cell as Point: One-Stage Framework for Efficient Cell Tracking","version":4},"reference_index":56,"source":"pdf_text","source_observed_at":"2026-08-12T14:53:01.535235Z"},"links":{"citing_paper":"/paper/2411.14833"},"observation_digest":"sha256:1f810ef2af5e667867b7ef04e1134ff5d984417ca5ca40bbf18a02914c1991a1","observation_id":"156a6a8b-85df-4cb4-872a-75da68e98912","resolution":{"observed_at":"2026-08-12T14:53:02.200793Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-12T14:53:02.186607Z","title":"The cell tracking challenge: 10 years of objective benchmarking.Nature Methods, pages 1010–1020, 2023","venue":null,"work_id":"b6a2efc3-eb3a-4008-8649-af815304e203","year":2023},"citing_paper":{"arxiv_id":"2411.14833","last_updated":"2026-07-03T07:34:00Z","snapshot_observed_at":"2026-08-18T10:54:44.358510Z","submitted_at":"2024-11-22T10:16:35Z","title":"Cell as Point: One-Stage Framework for Efficient Cell Tracking","version":4},"reference_index":57,"source":"pdf_text","source_observed_at":"2026-08-12T14:53:01.538740Z"},"links":{"citing_paper":"/paper/2411.14833"},"observation_digest":"sha256:f68dec4541323528811ff10c5acf8b536345cf8d3da937b91ccfe8ba9564e4a3","observation_id":"5ad24513-9a68-4037-ac8e-4a2070a3b2c3","resolution":{"observed_at":"2026-08-12T14:53:02.190287Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-12T14:53:02.175778Z","title":"Cell tracking accuracy measurement based on comparison of acyclic oriented graphs.PloS one, page e0144959, 2015","venue":null,"work_id":"2ab1159f-065d-43bd-968c-1ddc86ed63f0","year":2015},"citing_paper":{"arxiv_id":"2411.14833","last_updated":"2026-07-03T07:34:00Z","snapshot_observed_at":"2026-08-18T10:54:44.358510Z","submitted_at":"2024-11-22T10:16:35Z","title":"Cell as Point: One-Stage Framework for Efficient Cell Tracking","version":4},"reference_index":58,"source":"pdf_text","source_observed_at":"2026-08-12T14:53:01.542148Z"},"links":{"citing_paper":"/paper/2411.14833"},"observation_digest":"sha256:e2d0468ccab5fabb80c04b54a5836c4d105b03fdbc71fde5a0c963a4288ec354","observation_id":"48e32f44-e646-4c07-848b-5cf6ef52300b","resolution":{"observed_at":"2026-08-12T14:53:02.179742Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-12T14:53:02.165068Z","title":"Accurate cell tracking and lineage construction in live-cell imaging ex- periments with deep learning.Biorxiv, page 803205, 2019","venue":null,"work_id":"34be8d57-9e27-460c-9a2a-a229fac37164","year":2019},"citing_paper":{"arxiv_id":"2411.14833","last_updated":"2026-07-03T07:34:00Z","snapshot_observed_at":"2026-08-18T10:54:44.358510Z","submitted_at":"2024-11-22T10:16:35Z","title":"Cell as Point: One-Stage Framework for Efficient Cell Tracking","version":4},"reference_index":59,"source":"pdf_text","source_observed_at":"2026-08-12T14:53:01.545850Z"},"links":{"citing_paper":"/paper/2411.14833"},"observation_digest":"sha256:8ffd5fb107901ee08ebfdfce1d4d1147932358b692bb2864d91fa8f30232d090","observation_id":"9adbf80b-a467-4804-b9a0-9620d7b64066","resolution":{"observed_at":"2026-08-12T14:53:02.169197Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-12T14:53:02.154497Z","title":null,"venue":null,"work_id":"bbe116a3-25a6-4d6c-9a25-36c5826ba141","year":2024},"citing_paper":{"arxiv_id":"2411.14833","last_updated":"2026-07-03T07:34:00Z","snapshot_observed_at":"2026-08-18T10:54:44.358510Z","submitted_at":"2024-11-22T10:16:35Z","title":"Cell as Point: One-Stage Framework for Efficient Cell Tracking","version":4},"reference_index":60,"source":"pdf_text","source_observed_at":"2026-08-12T14:53:01.549451Z"},"links":{"citing_paper":"/paper/2411.14833"},"observation_digest":"sha256:f0cfd3cebacb24a4fb7e0108d78a4fe3ddf2fa690db87798f0fa87462dda7c39","observation_id":"7c8a5d2d-2276-4765-a9b3-4feef01544dd","resolution":{"observed_at":"2026-08-12T14:53:02.158396Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-12T14:53:02.143789Z","title":"Weakly-supervised cell tracking via backward-and-forward propagation","venue":null,"work_id":"d2ef2eac-266a-427f-909a-fb94d2dd07af","year":2020},"citing_paper":{"arxiv_id":"2411.14833","last_updated":"2026-07-03T07:34:00Z","snapshot_observed_at":"2026-08-18T10:54:44.358510Z","submitted_at":"2024-11-22T10:16:35Z","title":"Cell as Point: One-Stage Framework for Efficient Cell Tracking","version":4},"reference_index":61,"source":"pdf_text","source_observed_at":"2026-08-12T14:53:01.552760Z"},"links":{"citing_paper":"/paper/2411.14833"},"observation_digest":"sha256:9e61e1aa35279b9d85240652b961f37863f15b59a0bddc3d18303a546225d495","observation_id":"b424a6a9-b080-4b16-978a-abef6a1a3525","resolution":{"observed_at":"2026-08-12T14:53:02.147557Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-12T14:53:02.133099Z","title":"Distnet2d: Leveraging long-range temporal information for efficient segmentation and track- ing.PRX Life, page 023004, 2024","venue":null,"work_id":"f2efaa06-60e7-4929-aa38-e238128c0d09","year":2024},"citing_paper":{"arxiv_id":"2411.14833","last_updated":"2026-07-03T07:34:00Z","snapshot_observed_at":"2026-08-18T10:54:44.358510Z","submitted_at":"2024-11-22T10:16:35Z","title":"Cell as Point: One-Stage Framework for Efficient Cell Tracking","version":4},"reference_index":62,"source":"pdf_text","source_observed_at":"2026-08-12T14:53:01.556332Z"},"links":{"citing_paper":"/paper/2411.14833"},"observation_digest":"sha256:dc9c7a9ff59e4a84bcd7fd789e2281630f725a239f48febe783351d22e6176ed","observation_id":"fd371163-0a23-464f-94ab-33f096766587","resolution":{"observed_at":"2026-08-12T14:53:02.136652Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-12T14:53:02.122567Z","title":"Cell-tractr: A transformer-based model for end-to-end segmentation and tracking of cells.bioRxiv, pages 2024–07, 2024","venue":null,"work_id":"6359f466-fc85-415e-b7af-da0aaf2cc00f","year":2024},"citing_paper":{"arxiv_id":"2411.14833","last_updated":"2026-07-03T07:34:00Z","snapshot_observed_at":"2026-08-18T10:54:44.358510Z","submitted_at":"2024-11-22T10:16:35Z","title":"Cell as Point: One-Stage Framework for Efficient Cell Tracking","version":4},"reference_index":63,"source":"pdf_text","source_observed_at":"2026-08-12T14:53:01.560291Z"},"links":{"citing_paper":"/paper/2411.14833"},"observation_digest":"sha256:a4361c982e3fce23321939dd9b071c2c7be6473322f1050c33a7b31f2d790b57","observation_id":"01ecdb86-91a4-4a45-b105-960ed235b57f","resolution":{"observed_at":"2026-08-12T14:53:02.126526Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-12T14:53:02.111530Z","title":"Cell-tractr: A transformer-based model for end-to-end segmentation and tracking of cells.PLOS Computational Biology, page e1013071, 2025","venue":null,"work_id":"377ca86c-4964-410a-afb6-b71808c07ad8","year":2025},"citing_paper":{"arxiv_id":"2411.14833","last_updated":"2026-07-03T07:34:00Z","snapshot_observed_at":"2026-08-18T10:54:44.358510Z","submitted_at":"2024-11-22T10:16:35Z","title":"Cell as Point: One-Stage Framework for Efficient Cell Tracking","version":4},"reference_index":64,"source":"pdf_text","source_observed_at":"2026-08-12T14:53:01.563893Z"},"links":{"citing_paper":"/paper/2411.14833"},"observation_digest":"sha256:7bb318f07891c7b19b1087fae0dfafb54af8254882c93a05f55ee805e4532084","observation_id":"49c68b02-a99c-4728-9df6-b6a817f04973","resolution":{"observed_at":"2026-08-12T14:53:02.115597Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-12T14:53:02.100286Z","title":"Cou- pled minimum-cost flow cell tracking for high-throughput quantitative analysis.Medical image analysis, pages 650– 668, 2011","venue":null,"work_id":"2ca97fd0-d530-49c9-84c5-2942b901dc5f","year":2011},"citing_paper":{"arxiv_id":"2411.14833","last_updated":"2026-07-03T07:34:00Z","snapshot_observed_at":"2026-08-18T10:54:44.358510Z","submitted_at":"2024-11-22T10:16:35Z","title":"Cell as Point: One-Stage Framework for Efficient Cell Tracking","version":4},"reference_index":65,"source":"pdf_text","source_observed_at":"2026-08-12T14:53:01.567568Z"},"links":{"citing_paper":"/paper/2411.14833"},"observation_digest":"sha256:7da09ea83f427268e9bf694c63d7e916168dda07e7008c34b93d35eff63ab36a","observation_id":"9980c67c-a4e1-43f4-a8e2-7f275bb313c7","resolution":{"observed_at":"2026-08-12T14:53:02.104270Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-12T14:53:02.088676Z","title":"Instance segmentation and tracking with cosine embeddings and recurrent hourglass networks","venue":null,"work_id":"ce4729ef-b4c9-42f9-a80d-586f70c30131","year":null},"citing_paper":{"arxiv_id":"2411.14833","last_updated":"2026-07-03T07:34:00Z","snapshot_observed_at":"2026-08-18T10:54:44.358510Z","submitted_at":"2024-11-22T10:16:35Z","title":"Cell as Point: One-Stage Framework for Efficient Cell Tracking","version":4},"reference_index":66,"source":"pdf_text","source_observed_at":"2026-08-12T14:53:01.570945Z"},"links":{"citing_paper":"/paper/2411.14833"},"observation_digest":"sha256:05d16f14c857b7d015ec90c0bf0b2093620a4e82cd92979f759b56b90610570f","observation_id":"1cdc19e4-32b0-42fb-92ca-766b5424858a","resolution":{"observed_at":"2026-08-12T14:53:02.092629Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-12T14:53:02.077379Z","title":"J regularization improves imbalanced multiclass seg- mentation","venue":null,"work_id":"d55c8650-03c5-4e6a-9f2b-1f6135dddbe0","year":2020},"citing_paper":{"arxiv_id":"2411.14833","last_updated":"2026-07-03T07:34:00Z","snapshot_observed_at":"2026-08-18T10:54:44.358510Z","submitted_at":"2024-11-22T10:16:35Z","title":"Cell as Point: One-Stage Framework for Efficient Cell Tracking","version":4},"reference_index":67,"source":"pdf_text","source_observed_at":"2026-08-12T14:53:01.574784Z"},"links":{"citing_paper":"/paper/2411.14833"},"observation_digest":"sha256:43c03a56d902d86ea3f00992f5935d9fc06502a0eed9ea787410aa0040d14f2c","observation_id":"ece5fdcb-5913-428b-8d74-7a313e483eef","resolution":{"observed_at":"2026-08-12T14:53:02.081651Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-12T14:53:02.066340Z","title":"Cell lin- eage tracing in lens-free microscopy videos","venue":null,"work_id":"e9ce4540-88d9-457e-8a1c-557a03bd97e6","year":2017},"citing_paper":{"arxiv_id":"2411.14833","last_updated":"2026-07-03T07:34:00Z","snapshot_observed_at":"2026-08-18T10:54:44.358510Z","submitted_at":"2024-11-22T10:16:35Z","title":"Cell as Point: One-Stage Framework for Efficient Cell Tracking","version":4},"reference_index":68,"source":"pdf_text","source_observed_at":"2026-08-12T14:53:01.579249Z"},"links":{"citing_paper":"/paper/2411.14833"},"observation_digest":"sha256:55f168c65b9fdef77c3e5561b8fc475efb45463d0f7eea06f022167732f812f8","observation_id":"9ab4049d-ddf6-4ae8-878d-a76ba0eed923","resolution":{"observed_at":"2026-08-12T14:53:02.070105Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-12T14:53:02.054374Z","title":"Cell tracking and the development of cell-based therapies: a view from the cardiovascular cell therapy research network","venue":null,"work_id":"b0a746c9-2420-4ea5-bca3-7cad8f6433ca","year":2012},"citing_paper":{"arxiv_id":"2411.14833","last_updated":"2026-07-03T07:34:00Z","snapshot_observed_at":"2026-08-18T10:54:44.358510Z","submitted_at":"2024-11-22T10:16:35Z","title":"Cell as Point: One-Stage Framework for Efficient Cell Tracking","version":4},"reference_index":69,"source":"pdf_text","source_observed_at":"2026-08-12T14:53:01.583528Z"},"links":{"citing_paper":"/paper/2411.14833"},"observation_digest":"sha256:fde0e3a4496606e4e60971827e40f3aba94a3dae9dad8247d5cf454068bbc0e7","observation_id":"2a73466c-f261-4792-8f3b-39b5434a7cf8","resolution":{"observed_at":"2026-08-12T14:53:02.058518Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-12T14:53:02.042240Z","title":"Cell segmentation and tracking using cnn-based dis- tance predictions and a graph-based matching strategy.PLoS One, page e0243219, 2020","venue":null,"work_id":"b8d5351b-8100-4110-9b53-4e507ec21e90","year":2020},"citing_paper":{"arxiv_id":"2411.14833","last_updated":"2026-07-03T07:34:00Z","snapshot_observed_at":"2026-08-18T10:54:44.358510Z","submitted_at":"2024-11-22T10:16:35Z","title":"Cell as Point: One-Stage Framework for Efficient Cell Tracking","version":4},"reference_index":70,"source":"pdf_text","source_observed_at":"2026-08-12T14:53:01.588412Z"},"links":{"citing_paper":"/paper/2411.14833"},"observation_digest":"sha256:273ee9c9e1ac3b2edf5b7ffca29c136a63a02cca8da31be788850b3b071ca859","observation_id":"9ab73cef-5387-4851-afc8-1be0a24aace7","resolution":{"observed_at":"2026-08-12T14:53:02.046141Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-12T14:53:02.029577Z","title":"Omni- flow: Human omnidirectional optical flow","venue":null,"work_id":"41e74c0a-70e7-4994-b0f0-a717a45a34ce","year":2021},"citing_paper":{"arxiv_id":"2411.14833","last_updated":"2026-07-03T07:34:00Z","snapshot_observed_at":"2026-08-18T10:54:44.358510Z","submitted_at":"2024-11-22T10:16:35Z","title":"Cell as Point: One-Stage Framework for Efficient Cell Tracking","version":4},"reference_index":71,"source":"pdf_text","source_observed_at":"2026-08-12T14:53:01.592281Z"},"links":{"citing_paper":"/paper/2411.14833"},"observation_digest":"sha256:804b2e89e1eb8f3186e9e75655817343762a180d4bd5a5f4a44fa67ce6567ef7","observation_id":"611db1ab-0600-45ac-b4db-1d8011f16a70","resolution":{"observed_at":"2026-08-12T14:53:02.033922Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-12T14:53:02.016862Z","title":"Bayesian tracking for fluorescence microscopic imaging","venue":null,"work_id":"85933db6-7529-461d-a6d1-805e6a714501","year":2006},"citing_paper":{"arxiv_id":"2411.14833","last_updated":"2026-07-03T07:34:00Z","snapshot_observed_at":"2026-08-18T10:54:44.358510Z","submitted_at":"2024-11-22T10:16:35Z","title":"Cell as Point: One-Stage Framework for Efficient Cell Tracking","version":4},"reference_index":72,"source":"pdf_text","source_observed_at":"2026-08-12T14:53:01.596706Z"},"links":{"citing_paper":"/paper/2411.14833"},"observation_digest":"sha256:dc6a069490be346ed2e421806cc2b6d2e2b1d1b56aca3bdb456dccad0286674d","observation_id":"dab6111b-d449-4fba-9265-e6748b663c4e","resolution":{"observed_at":"2026-08-12T14:53:02.020962Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-12T14:53:02.004832Z","title":"Fuzzy-based propaga- tion of prior knowledge to improve large-scale image analy- sis pipelines.Plos one, page e0187535, 2017","venue":null,"work_id":"c3c94b37-ba64-4b25-9e28-494373ea921c","year":2017},"citing_paper":{"arxiv_id":"2411.14833","last_updated":"2026-07-03T07:34:00Z","snapshot_observed_at":"2026-08-18T10:54:44.358510Z","submitted_at":"2024-11-22T10:16:35Z","title":"Cell as Point: One-Stage Framework for Efficient Cell Tracking","version":4},"reference_index":73,"source":"pdf_text","source_observed_at":"2026-08-12T14:53:01.600560Z"},"links":{"citing_paper":"/paper/2411.14833"},"observation_digest":"sha256:d5d61ee88fa172f02af3635f852b02971ebfc62626d61fb9b50d5af29dfa1754","observation_id":"9e3509e9-cd4b-47af-b582-fe7fe13fd132","resolution":{"observed_at":"2026-08-12T14:53:02.008916Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-12T14:53:01.993294Z","title":"Cellpose: a generalist algorithm for cellular segmentation.Nature methods, pages 100–106, 2021","venue":null,"work_id":"10ba46f4-a8d1-48b3-b57f-c8de551f6d00","year":2021},"citing_paper":{"arxiv_id":"2411.14833","last_updated":"2026-07-03T07:34:00Z","snapshot_observed_at":"2026-08-18T10:54:44.358510Z","submitted_at":"2024-11-22T10:16:35Z","title":"Cell as Point: One-Stage Framework for Efficient Cell Tracking","version":4},"reference_index":74,"source":"pdf_text","source_observed_at":"2026-08-12T14:53:01.604444Z"},"links":{"citing_paper":"/paper/2411.14833"},"observation_digest":"sha256:cfee57eef367f398b60afc21fddd108bd25548a0aa466e5028fb2ed9560b0c0c","observation_id":"4866cbdf-6618-4935-9b6c-dcc0c551c52c","resolution":{"observed_at":"2026-08-12T14:53:01.997400Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-12T14:53:01.608294Z","title":"Pwc-net: Cnns for optical flow using pyramid, warping, and cost volume","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2411.14833","last_updated":"2026-07-03T07:34:00Z","snapshot_observed_at":"2026-08-18T10:54:44.358510Z","submitted_at":"2024-11-22T10:16:35Z","title":"Cell as Point: One-Stage Framework for Efficient Cell Tracking","version":4},"reference_index":75,"source":"pdf_text","source_observed_at":"2026-08-12T14:53:01.608294Z"},"links":{"citing_paper":"/paper/2411.14833"},"observation_digest":"sha256:2c6d4815689c3195767fdf980ae030166ed5a9c56e564ab48d5c8d7791991bb1","observation_id":"a1f9073a-48c0-49be-9916-a988b66f7f56","resolution":{"observed_at":"2026-08-12T14:53:01.608294Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T14:53:01.612130Z","title":"Raft: Recurrent all-pairs field transforms for optical flow","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2411.14833","last_updated":"2026-07-03T07:34:00Z","snapshot_observed_at":"2026-08-18T10:54:44.358510Z","submitted_at":"2024-11-22T10:16:35Z","title":"Cell as Point: One-Stage Framework for Efficient Cell Tracking","version":4},"reference_index":76,"source":"pdf_text","source_observed_at":"2026-08-12T14:53:01.612130Z"},"links":{"citing_paper":"/paper/2411.14833"},"observation_digest":"sha256:a91a7e2f63ac66ceb27141e6230fbb559758d85c228664892d01111b6bafe174","observation_id":"af90e4aa-6295-4bb8-b81e-2e49556d9fcb","resolution":{"observed_at":"2026-08-12T14:53:01.612130Z","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":"2026-08-12T14:53:01.968998Z","title":"Automated cell tracking using 3d nnunet and light sheet microscopy to quantify regional deformation in zebrafish.bioRxiv, 2024","venue":null,"work_id":"d7c4583d-3a08-40c2-8644-be14f33db6d8","year":2024},"citing_paper":{"arxiv_id":"2411.14833","last_updated":"2026-07-03T07:34:00Z","snapshot_observed_at":"2026-08-18T10:54:44.358510Z","submitted_at":"2024-11-22T10:16:35Z","title":"Cell as Point: One-Stage Framework for Efficient Cell Tracking","version":4},"reference_index":77,"source":"pdf_text","source_observed_at":"2026-08-12T14:53:01.615836Z"},"links":{"citing_paper":"/paper/2411.14833"},"observation_digest":"sha256:38f74cb2bc56473c7d516b6fe18f1c3f39477b1a2e450d5fb20bdedd268c61f3","observation_id":"f47e69d1-8c36-4ae0-87c5-7a9d7d8cea17","resolution":{"observed_at":"2026-08-12T14:53:01.972764Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-12T14:53:01.956750Z","title":"Network flow integer program- ming to track elliptical cells in time-lapse sequences.IEEE Transactions on Medical Imaging, pages 942–951, 2016","venue":null,"work_id":"acdf5d3f-db74-4b37-b82a-3ff232de60aa","year":2016},"citing_paper":{"arxiv_id":"2411.14833","last_updated":"2026-07-03T07:34:00Z","snapshot_observed_at":"2026-08-18T10:54:44.358510Z","submitted_at":"2024-11-22T10:16:35Z","title":"Cell as Point: One-Stage Framework for Efficient Cell Tracking","version":4},"reference_index":78,"source":"pdf_text","source_observed_at":"2026-08-12T14:53:01.619590Z"},"links":{"citing_paper":"/paper/2411.14833"},"observation_digest":"sha256:46c68169924d1eb9f8e2383a57714a648b2e9be504cafc32a721a84dfc182d76","observation_id":"1bf902c4-06b5-474d-899a-8be811283e67","resolution":{"observed_at":"2026-08-12T14:53:01.961374Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-12T14:53:01.944755Z","title":"Automated deep lineage tree analysis using a bayesian single cell tracking approach.Frontiers in Com- puter Science, 3:734559, 2021","venue":null,"work_id":"33945282-8fe6-4871-9de7-6547fe517cff","year":2021},"citing_paper":{"arxiv_id":"2411.14833","last_updated":"2026-07-03T07:34:00Z","snapshot_observed_at":"2026-08-18T10:54:44.358510Z","submitted_at":"2024-11-22T10:16:35Z","title":"Cell as Point: One-Stage Framework for Efficient Cell Tracking","version":4},"reference_index":79,"source":"pdf_text","source_observed_at":"2026-08-12T14:53:01.623141Z"},"links":{"citing_paper":"/paper/2411.14833"},"observation_digest":"sha256:8925d6693b0fe2871fe221566e2e719e01c9833ffd5a84f1635ecb775d234711","observation_id":"4eec071f-ed7a-4a4a-a8fa-d8b6f70ea702","resolution":{"observed_at":"2026-08-12T14:53:01.948710Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-12T14:53:01.933535Z","title":"An objective comparison of cell-tracking algorithms.Nature methods, pages 1141–1152, 2017","venue":null,"work_id":"7f6f3729-5009-4d6b-9c87-5af90dea228b","year":2017},"citing_paper":{"arxiv_id":"2411.14833","last_updated":"2026-07-03T07:34:00Z","snapshot_observed_at":"2026-08-18T10:54:44.358510Z","submitted_at":"2024-11-22T10:16:35Z","title":"Cell as Point: One-Stage Framework for Efficient Cell Tracking","version":4},"reference_index":80,"source":"pdf_text","source_observed_at":"2026-08-12T14:53:01.626779Z"},"links":{"citing_paper":"/paper/2411.14833"},"observation_digest":"sha256:361c7e1ea634348546f28036c36a833b3e938763fc378ad93687b07ef8c8c90d","observation_id":"b5e16caa-3756-47a4-a13e-e2c5e77b85b4","resolution":{"observed_at":"2026-08-12T14:53:01.937612Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-12T14:53:01.630506Z","title":"Attention is all you need","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2411.14833","last_updated":"2026-07-03T07:34:00Z","snapshot_observed_at":"2026-08-18T10:54:44.358510Z","submitted_at":"2024-11-22T10:16:35Z","title":"Cell as Point: One-Stage Framework for Efficient Cell Tracking","version":4},"reference_index":81,"source":"pdf_text","source_observed_at":"2026-08-12T14:53:01.630506Z"},"links":{"citing_paper":"/paper/2411.14833"},"observation_digest":"sha256:fcdecddd2f88361041d0b25841fde173a4a25555859b93bfe4cb62a5fa954cfb","observation_id":"910cdb94-6344-4668-bebe-20b7dbb2666b","resolution":{"observed_at":"2026-08-12T14:53:01.630506Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T14:53:01.634325Z","title":"Tracking everything everywhere all at once","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2411.14833","last_updated":"2026-07-03T07:34:00Z","snapshot_observed_at":"2026-08-18T10:54:44.358510Z","submitted_at":"2024-11-22T10:16:35Z","title":"Cell as Point: One-Stage Framework for Efficient Cell Tracking","version":4},"reference_index":82,"source":"pdf_text","source_observed_at":"2026-08-12T14:53:01.634325Z"},"links":{"citing_paper":"/paper/2411.14833"},"observation_digest":"sha256:a464dc16fa71e8d05ac39ec2538af0f9c1367097e11ce847ec47072cc1871fb3","observation_id":"e327f715-a898-4aba-8f54-373f73a6161d","resolution":{"observed_at":"2026-08-12T14:53:01.634325Z","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":"2026-08-12T14:53:01.908680Z","title":"Cris: Clip- driven referring image segmentation","venue":null,"work_id":"706b0c5c-0f54-4d7d-a40f-f2403e40b786","year":2022},"citing_paper":{"arxiv_id":"2411.14833","last_updated":"2026-07-03T07:34:00Z","snapshot_observed_at":"2026-08-18T10:54:44.358510Z","submitted_at":"2024-11-22T10:16:35Z","title":"Cell as Point: One-Stage Framework for Efficient Cell Tracking","version":4},"reference_index":83,"source":"pdf_text","source_observed_at":"2026-08-12T14:53:01.638382Z"},"links":{"citing_paper":"/paper/2411.14833"},"observation_digest":"sha256:8e9ebaf2d326fc4a37f58affbfbb65b7d237692109215d09a2811730adc02c38","observation_id":"5903b2ff-f5bb-43e2-9768-30aad53496d7","resolution":{"observed_at":"2026-08-12T14:53:01.912242Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-12T14:53:01.897732Z","title":"Star-convex polyhedra for 3d object detec- tion and segmentation in microscopy","venue":null,"work_id":"3676d606-3356-4c62-9564-f2846fc88db7","year":2020},"citing_paper":{"arxiv_id":"2411.14833","last_updated":"2026-07-03T07:34:00Z","snapshot_observed_at":"2026-08-18T10:54:44.358510Z","submitted_at":"2024-11-22T10:16:35Z","title":"Cell as Point: One-Stage Framework for Efficient Cell Tracking","version":4},"reference_index":84,"source":"pdf_text","source_observed_at":"2026-08-12T14:53:01.642103Z"},"links":{"citing_paper":"/paper/2411.14833"},"observation_digest":"sha256:9253466901ade58fbadd962c314e3a318e1820b3eb6149bef99b5448b66ae6c4","observation_id":"5c6dc98c-6dd0-4f66-a414-bea386e0bcae","resolution":{"observed_at":"2026-08-12T14:53:01.901418Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-12T14:53:01.886815Z","title":"Unsupervised learning of object-centric embeddings for cell instance segmentation in microscopy images","venue":null,"work_id":"1d590b75-dc1c-4cbf-ab34-772daabc4a1b","year":2023},"citing_paper":{"arxiv_id":"2411.14833","last_updated":"2026-07-03T07:34:00Z","snapshot_observed_at":"2026-08-18T10:54:44.358510Z","submitted_at":"2024-11-22T10:16:35Z","title":"Cell as Point: One-Stage Framework for Efficient Cell Tracking","version":4},"reference_index":85,"source":"pdf_text","source_observed_at":"2026-08-12T14:53:01.645934Z"},"links":{"citing_paper":"/paper/2411.14833"},"observation_digest":"sha256:4843069f139c6dc721bb10ebccd1731e9d9464610f42025e76a7b3f59b494bd0","observation_id":"fe2aac7d-4285-44e0-b8ec-2e1416e39e6f","resolution":{"observed_at":"2026-08-12T14:53:01.890895Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-12T14:53:01.875439Z","title":"Accurate optical flow via direct cost volume processing","venue":null,"work_id":"0b31ceee-05d3-434d-bd2d-9613edaa27dd","year":2017},"citing_paper":{"arxiv_id":"2411.14833","last_updated":"2026-07-03T07:34:00Z","snapshot_observed_at":"2026-08-18T10:54:44.358510Z","submitted_at":"2024-11-22T10:16:35Z","title":"Cell as Point: One-Stage Framework for Efficient Cell Tracking","version":4},"reference_index":86,"source":"pdf_text","source_observed_at":"2026-08-12T14:53:01.649682Z"},"links":{"citing_paper":"/paper/2411.14833"},"observation_digest":"sha256:dc6a8b833f99f47aeb7ef8bc29ab6263da1c45eb7574ad0f6e9fd69ef1784902","observation_id":"caaf8bd3-1313-4bfa-a366-f0e8608e7997","resolution":{"observed_at":"2026-08-12T14:53:01.879574Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-12T14:53:01.864254Z","title":"Spatial- temporal relation networks for multi-object tracking","venue":null,"work_id":"cf840194-abed-43ad-aa97-ba0c18d61439","year":2019},"citing_paper":{"arxiv_id":"2411.14833","last_updated":"2026-07-03T07:34:00Z","snapshot_observed_at":"2026-08-18T10:54:44.358510Z","submitted_at":"2024-11-22T10:16:35Z","title":"Cell as Point: One-Stage Framework for Efficient Cell Tracking","version":4},"reference_index":87,"source":"pdf_text","source_observed_at":"2026-08-12T14:53:01.653282Z"},"links":{"citing_paper":"/paper/2411.14833"},"observation_digest":"sha256:30302ce232e8f6f45debb38e464c622b53c4656885ce32c0e84a3fee549e9a29","observation_id":"18e35e23-1eec-415f-be6a-383dfdb830ad","resolution":{"observed_at":"2026-08-12T14:53:01.868333Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-12T14:53:01.852954Z","title":"Cell segmentation, tracking, and mitosis detection using temporal context","venue":null,"work_id":"9ba8ca04-4fef-4f44-9fb8-4b68b0dd064e","year":2005},"citing_paper":{"arxiv_id":"2411.14833","last_updated":"2026-07-03T07:34:00Z","snapshot_observed_at":"2026-08-18T10:54:44.358510Z","submitted_at":"2024-11-22T10:16:35Z","title":"Cell as Point: One-Stage Framework for Efficient Cell Tracking","version":4},"reference_index":88,"source":"pdf_text","source_observed_at":"2026-08-12T14:53:01.657871Z"},"links":{"citing_paper":"/paper/2411.14833"},"observation_digest":"sha256:42b02684aa03960fb22193191eae3452a83b147ae7230543343e46d3a4cdc5a9","observation_id":"a5317d42-72fb-42a3-b27a-73ee702f288e","resolution":{"observed_at":"2026-08-12T14:53:01.856904Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-12T14:53:01.841748Z","title":"Deep learning in medical image super resolution: a review.Applied Intelligence, pages 20891–20916, 2023","venue":null,"work_id":"233a830b-5c04-4de6-94b7-8459d5c1a105","year":2023},"citing_paper":{"arxiv_id":"2411.14833","last_updated":"2026-07-03T07:34:00Z","snapshot_observed_at":"2026-08-18T10:54:44.358510Z","submitted_at":"2024-11-22T10:16:35Z","title":"Cell as Point: One-Stage Framework for Efficient Cell Tracking","version":4},"reference_index":89,"source":"pdf_text","source_observed_at":"2026-08-12T14:53:01.661445Z"},"links":{"citing_paper":"/paper/2411.14833"},"observation_digest":"sha256:fe165c0a73ccb4dcaaecfbbd5e8243a631d55c0be69b56c80951a57284a89742","observation_id":"259c6b7a-5414-479e-bd2d-55d36259dfc4","resolution":{"observed_at":"2026-08-12T14:53:01.845495Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-12T14:53:01.829952Z","title":"Prediction of sequen- tial organelles localization under imbalance using a balanced deep u-net.Scientific reports, page 2626, 2020","venue":null,"work_id":"b764aabc-3680-49fc-adca-526dcfc6e414","year":2020},"citing_paper":{"arxiv_id":"2411.14833","last_updated":"2026-07-03T07:34:00Z","snapshot_observed_at":"2026-08-18T10:54:44.358510Z","submitted_at":"2024-11-22T10:16:35Z","title":"Cell as Point: One-Stage Framework for Efficient Cell Tracking","version":4},"reference_index":90,"source":"pdf_text","source_observed_at":"2026-08-12T14:53:01.665281Z"},"links":{"citing_paper":"/paper/2411.14833"},"observation_digest":"sha256:5a097540326dd61e2fff0dcba051e0004fb358e0385e4016630dc32be03e91e0","observation_id":"152d1b2e-7f99-4725-925b-cc81bae23134","resolution":{"observed_at":"2026-08-12T14:53:01.834227Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-12T14:53:01.816518Z","title":"Optical flow and scene flow estimation: A survey","venue":null,"work_id":"75f00b45-e99b-41a2-a6f6-b168f072224b","year":2021},"citing_paper":{"arxiv_id":"2411.14833","last_updated":"2026-07-03T07:34:00Z","snapshot_observed_at":"2026-08-18T10:54:44.358510Z","submitted_at":"2024-11-22T10:16:35Z","title":"Cell as Point: One-Stage Framework for Efficient Cell Tracking","version":4},"reference_index":91,"source":"pdf_text","source_observed_at":"2026-08-12T14:53:01.669216Z"},"links":{"citing_paper":"/paper/2411.14833"},"observation_digest":"sha256:e5b3642037b0323713c6116eeb8a81b6cdbaedf3c082b91893a881855fd8ce25","observation_id":"b0803307-f676-47d4-b93e-d04e6c68aad7","resolution":{"observed_at":"2026-08-12T14:53:01.820768Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-12T14:53:01.803764Z","title":"Unsupervised 3d end-to-end medical image registration with volume tweening network.IEEE Journal of Biomedical and Health Informatics, pages 1394–1404, 2020","venue":null,"work_id":"3de16662-134d-4e56-84a2-0b203cff2d24","year":2020},"citing_paper":{"arxiv_id":"2411.14833","last_updated":"2026-07-03T07:34:00Z","snapshot_observed_at":"2026-08-18T10:54:44.358510Z","submitted_at":"2024-11-22T10:16:35Z","title":"Cell as Point: One-Stage Framework for Efficient Cell Tracking","version":4},"reference_index":92,"source":"pdf_text","source_observed_at":"2026-08-12T14:53:01.672828Z"},"links":{"citing_paper":"/paper/2411.14833"},"observation_digest":"sha256:c5c0812141077979c8f615c622d97bc738c699bd26e20bb834409a20171507ca","observation_id":"1cfa1c21-253d-4843-aa5d-cb21b9927085","resolution":{"observed_at":"2026-08-12T14:53:01.808432Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-12T14:53:01.790856Z","title":"Harley, Bokui Shen, Gordon Wet- zstein, and Leonidas J","venue":null,"work_id":"a91cc6d2-6d99-4b06-b958-988aa84ab921","year":2023},"citing_paper":{"arxiv_id":"2411.14833","last_updated":"2026-07-03T07:34:00Z","snapshot_observed_at":"2026-08-18T10:54:44.358510Z","submitted_at":"2024-11-22T10:16:35Z","title":"Cell as Point: One-Stage Framework for Efficient Cell Tracking","version":4},"reference_index":93,"source":"pdf_text","source_observed_at":"2026-08-12T14:53:01.676913Z"},"links":{"citing_paper":"/paper/2411.14833"},"observation_digest":"sha256:fd942655332eef8e5ac47b820e66f70b5280e6f3acf7a1f4e84efc47a1fbe084","observation_id":"5c381d63-c1f4-4216-99ba-8655c8a1ee2e","resolution":{"observed_at":"2026-08-12T14:53:01.794966Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-12T14:53:01.774948Z","title":"Joint multi-frame detection and segmentation for multi-cell tracking","venue":null,"work_id":"0959ccbc-58dc-48ca-a17a-b1fd8a80f25c","year":2019},"citing_paper":{"arxiv_id":"2411.14833","last_updated":"2026-07-03T07:34:00Z","snapshot_observed_at":"2026-08-18T10:54:44.358510Z","submitted_at":"2024-11-22T10:16:35Z","title":"Cell as Point: One-Stage Framework for Efficient Cell Tracking","version":4},"reference_index":94,"source":"pdf_text","source_observed_at":"2026-08-12T14:53:01.680876Z"},"links":{"citing_paper":"/paper/2411.14833"},"observation_digest":"sha256:c7ab1725bd4aaab6c5dc5df0c4bcbe90d46aa37528ffda5295cd60d0f56bdaee","observation_id":"c8a4d22d-e368-47da-b90b-95a9a4b1502b","resolution":{"observed_at":"2026-08-12T14:53:01.780897Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-12T14:53:01.762541Z","title":null,"venue":null,"work_id":"30b7a186-2d35-47cb-94b5-d65a16bf633c","year":2019},"citing_paper":{"arxiv_id":"2411.14833","last_updated":"2026-07-03T07:34:00Z","snapshot_observed_at":"2026-08-18T10:54:44.358510Z","submitted_at":"2024-11-22T10:16:35Z","title":"Cell as Point: One-Stage Framework for Efficient Cell Tracking","version":4},"reference_index":446,"source":"pdf_text","source_observed_at":"2026-08-12T14:53:01.685095Z"},"links":{"citing_paper":"/paper/2411.14833"},"observation_digest":"sha256:cc77a4d9d604eada1e28c6d09211cf40da64e13a12b10b24404561df1e3a5f13","observation_id":"0eb53047-747e-4072-9b57-d6628591f023","resolution":{"observed_at":"2026-08-12T14:53:01.766743Z","resolver_source":"raw_fallback","status":"parse_uncertain"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-12T14:53:01.353165Z","title":"6, 9, 10","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2411.14833","last_updated":"2026-07-03T07:34:00Z","snapshot_observed_at":"2026-08-18T10:54:44.358510Z","submitted_at":"2024-11-22T10:16:35Z","title":"Cell as Point: One-Stage Framework for Efficient Cell Tracking","version":4},"reference_index":626,"source":"pdf_text","source_observed_at":"2026-08-12T14:53:01.353165Z"},"links":{"citing_paper":"/paper/2411.14833"},"observation_digest":"sha256:3d3586c149ceef4b357552e0ebc109c9d40e950da61ec34ff982f4b174d0d51b","observation_id":"0297a972-804a-4cb6-8680-5946085d4da1","resolution":{"observed_at":"2026-08-12T14:53:01.353165Z","resolver_source":null,"status":"parse_uncertain"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2411.14833","last_updated":"2026-07-03T07:34:00Z","latest_version":4,"primary_category":"eess.IV","snapshot_observed_at":"2026-08-18T10:54:44.358510Z","submitted_at":"2024-11-22T10:16:35Z","title":"Cell as Point: One-Stage Framework for Efficient Cell Tracking"},"reference_resolution":{"displayed":96,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":2,"unresolved":24,"verified_exact":1,"verified_fuzzy":69},"total_outbound_references":96},"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":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"thesis":"As of 19 August 2026, this Paper Citation Record lists 96 of 96 outbound references and 1 inbound Pith citation observation for arXiv:2411.14833."}