Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-06T21:29:02.824750Z
Paper Citation Record · LEDGER
As of 7 August 2026, this Paper Citation Record lists 29 of 29 outbound references and 1 inbound Pith citation observation for arXiv:2506.24039.
A citation records a reference. It does not transfer a finding from one paper to another.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-06T21:29:02.824750Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-05-12T01:18:11.157463Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-12T08:06:29.312410Z
29 of 29 outbound references displayed
External citation measurements
No source-named external measurement is stored.
Observation 760da727-d9b4-4d0b-a4be-0a583d5aff16 · outbound
Foundation Models for Zero-Shot Segmentation of Scientific Images without AI-Ready Data Segment anything for microscopy
Reference 1
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Reference 2
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Observation 818ca449-fd51-433e-8b39-9c5efe32374d · outbound
Foundation Models for Zero-Shot Segmentation of Scientific Images without AI-Ready Data Carpenter, Thouis R
Reference 3
Source-reported events for the cited work
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Observation 57c81d51-c1dd-4421-99d7-fec9d9f18824 · outbound
Foundation Models for Zero-Shot Segmentation of Scientific Images without AI-Ready Data Lienkamp, Thomas Brox, and Olaf Ronneberger
Reference 4
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Foundation Models for Zero-Shot Segmentation of Scientific Images without AI-Ready Data Measures of the amount of ecologic as- sociation between species
Reference 5
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Observation 99a1e18b-a48f-4b55-8632-10b1cceea941 · outbound
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Reference 6
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Observation 5699695b-6e22-4cc2-892c-df318dc57328 · outbound
Foundation Models for Zero-Shot Segmentation of Scientific Images without AI-Ready Data Achieving the hydrogen shot: Interrogating ionomer interfaces
Reference 7
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Observation dcf72ca6-863b-45cd-a54f-932a03bb1327 · outbound
Foundation Models for Zero-Shot Segmentation of Scientific Images without AI-Ready Data Deep learning analysis on microscopic imag- ing in materials science
Reference 8
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Observation 5bb08689-1f96-403d-b57d-3b2658344c61 · outbound
Foundation Models for Zero-Shot Segmentation of Scientific Images without AI-Ready Data VISTA3D: A Unified Segmenta- tion Foundation Model For 3D Medical Imaging
Reference 9
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Reference 10
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Observation 6d66a785-94cb-4f7d-afdf-d262ea0a95dc · outbound
Foundation Models for Zero-Shot Segmentation of Scientific Images without AI-Ready Data Referitgame: Referring to objects in photographs of natural scenes
Reference 11
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Observation b95a0afb-92f2-4760-a5f1-0ea9568eeeb5 · outbound
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Reference 12
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Foundation Models for Zero-Shot Segmentation of Scientific Images without AI-Ready Data Computer visualization of three-dimensional image data using imod
Reference 13
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Reference 14
Source-reported events for the cited work
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Foundation Models for Zero-Shot Segmentation of Scientific Images without AI-Ready Data Brickdl: Graph- level optimizations for dnns with fine-grained data blocking on gpus
Reference 15
Source-reported events for the cited work
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Observation 86b8710e-b5e9-4197-b8c3-20fba41e559c · outbound
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Reference 16
Source-reported events for the cited work
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Observation 9392f639-09cf-4a10-bd04-f01252889e86 · outbound
Foundation Models for Zero-Shot Segmentation of Scientific Images without AI-Ready Data Image Segmentation Using Text and Image Prompts
Reference 17
Source-reported events for the cited work
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Observation 01a7f6ae-ea98-40cf-9ab0-a80f451e19fa · outbound
Foundation Models for Zero-Shot Segmentation of Scientific Images without AI-Ready Data Segment anything in medical images
Reference 18
Source-reported events for the cited work
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Foundation Models for Zero-Shot Segmentation of Scientific Images without AI-Ready Data Mazurowski, Haoyu Dong, Han Gu, Jichen Yang, Nicholas Saha, and Jiarui Luo
Reference 19
Source-reported events for the cited work
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Reference 21
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Foundation Models for Zero-Shot Segmentation of Scientific Images without AI-Ready Data Nih image to imagej: 25 years of image analysis
Reference 22
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Reference 23
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Foundation Models for Zero-Shot Segmentation of Scientific Images without AI-Ready Data Interactive medical image segmentation using deep learning with image-specific fine tuning
Reference 24
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Observation 545e7e6c-922f-4132-ba0c-71dcfb0af567 · outbound
Foundation Models for Zero-Shot Segmentation of Scientific Images without AI-Ready Data Deepigeos: a deep interactive geodesic frame- work for medical image segmentation
Reference 25
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Observation dd378ec7-0537-45de-9032-ef3c027ed0cd · outbound
Foundation Models for Zero-Shot Segmentation of Scientific Images without AI-Ready Data Ushizima, Victor C
Reference 26
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Observation 24d08a7b-0c8a-4350-b8b4-dc015fc8d815 · outbound
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Reference 27
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Observation e365f2fe-1e37-435c-bb81-dfbd1172a0c6 · outbound
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Reference 28
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Reference 29
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Reference 29
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