Paper Citation Record · LEDGER

Universal CT Representations from Anatomy to Disease Phenotype through Agglomerative Pretraining

As of 7 August 2026, this Paper Citation Record lists 18 of 18 outbound references and 1 inbound Pith citation observation for arXiv:2605.21906.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2605.21906 v2

Coverage vector

measured 18 of 18 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-05-25T06:16:48.755086Z

measured 19 of 19 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-06T06:34:29.942622+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-01T03:19:39.259982Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

18 of 18 outbound references displayed

verified exact13
verified fuzzy2
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch3

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 033edfe1-9024-4519-9e06-09474e3f084c · outbound

This paper cites MONAI: An open-source framework for deep learning in healthcare.

Universal CT Representations from Anatomy to Disease Phenotype through Agglomerative Pretraining MONAI: An open-source framework for deep learning in healthcare

Reference 1

Resolution: verified exact; local_arxiv, observed 2026-05-25T06:20:24.487441Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 4dfee9cf-5833-4a2b-9623-88d57fdaf4bf · outbound

This paper cites Scaling self-supervised and cross-modal pretraining for volumetric ct transformers.

Universal CT Representations from Anatomy to Disease Phenotype through Agglomerative Pretraining Scaling self-supervised and cross-modal pretraining for volumetric ct transformers

Reference 2

Resolution: verified exact; arxiv_id, observed 2026-05-25T06:20:24.493675Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 932361e9-a8d9-4429-8a05-cb3f0d8fe772 · outbound

This paper cites Curia: A Multi-Modal Foundation Model for Radiology.

Universal CT Representations from Anatomy to Disease Phenotype through Agglomerative Pretraining Curia: A Multi-Modal Foundation Model for Radiology

Reference 3

Resolution: metadata mismatch; arxiv_id, observed 2026-05-25T06:20:24.475861Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation b79fdc5d-7ec8-4473-81c9-caf2d384de8d · outbound

This paper cites Vision Transformers Need Registers.

Universal CT Representations from Anatomy to Disease Phenotype through Agglomerative Pretraining Vision Transformers Need Registers

Reference 4

Resolution: verified exact; local_arxiv, observed 2026-05-25T06:20:24.464451Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 7ee30f1f-6b40-4915-b9c4-fcd7c5c27d05 · outbound

This paper cites An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale.

Universal CT Representations from Anatomy to Disease Phenotype through Agglomerative Pretraining An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 5

Resolution: verified exact; local_arxiv, observed 2026-05-25T06:20:24.507043Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 568eb556-f38d-4c48-9fb9-1ccf9fba7dbe · outbound

This paper cites semanticscholar.org/CorpusID:208547601.

Universal CT Representations from Anatomy to Disease Phenotype through Agglomerative Pretraining semanticscholar.org/CorpusID:208547601

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T10:16:53.585806Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation e72b48a1-34e0-41f6-bed7-5785a1db89c4 · outbound

This paper cites Fabian Isensee, Paul F Jaeger, Simon AA Kohl, Jens Petersen, and Klaus H Maier-Hein.

Universal CT Representations from Anatomy to Disease Phenotype through Agglomerative Pretraining Fabian Isensee, Paul F Jaeger, Simon AA Kohl, Jens Petersen, and Klaus H Maier-Hein

Reference 7

Resolution: verified exact; doi, observed 2026-05-25T06:20:24.161296Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation f9f74932-a0cd-4bc0-8a0f-06add8cf6a3b · outbound

This paper cites Automatic Organ and Pan-cancer Segmentation in Abdomen CT: the FLARE 2023 Challenge.

Universal CT Representations from Anatomy to Disease Phenotype through Agglomerative Pretraining Automatic Organ and Pan-cancer Segmentation in Abdomen CT: the FLARE 2023 Challenge

Reference 8

Resolution: verified exact; arxiv_id, observed 2026-05-25T06:20:24.453418Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 713e2c36-bf72-4660-9dda-189ac6f17948 · outbound

This paper cites TIPS: Text-Image Pretraining with Spatial awareness.

Universal CT Representations from Anatomy to Disease Phenotype through Agglomerative Pretraining TIPS: Text-Image Pretraining with Spatial awareness

Reference 9

Resolution: verified exact; arxiv_id, observed 2026-05-25T06:20:24.499844Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 5e00c399-7a1a-4d46-8f05-3018500b253e · outbound

This paper cites DINOv2: Learning Robust Visual Features without Supervision.

Universal CT Representations from Anatomy to Disease Phenotype through Agglomerative Pretraining DINOv2: Learning Robust Visual Features without Supervision

Reference 10

Resolution: verified exact; local_arxiv, observed 2026-05-25T06:20:24.513102Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 0077be65-aedf-46ef-a98e-3f0e86d87db9 · outbound

This paper cites Vision Foundation Models for Computed Tomography.

Universal CT Representations from Anatomy to Disease Phenotype through Agglomerative Pretraining Vision Foundation Models for Computed Tomography

Reference 11

Resolution: verified exact; arxiv_id, observed 2026-05-25T06:20:24.481937Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation bcd32a76-0396-4986-b084-1fc011a695c6 · outbound

This paper cites DINOv3.

Universal CT Representations from Anatomy to Disease Phenotype through Agglomerative Pretraining DINOv3

Reference 12

Resolution: metadata mismatch; local_arxiv, observed 2026-05-25T06:20:24.469680Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 224893dc-a9f5-4dda-a747-6aa803b8e652 · outbound

This paper cites Trends in use of medical imaging in us health care systems and in ontario, canada, 2000-2016.

Universal CT Representations from Anatomy to Disease Phenotype through Agglomerative Pretraining Trends in use of medical imaging in us health care systems and in ontario, canada, 2000-2016

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T10:16:53.589416Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation f350a914-2e37-4e6e-b55b-c44c255e56ae · outbound

This paper cites Com- prehensive language-image pre-training for 3d medical image understanding.arXiv preprint arXiv:2510.15042, 2025a.

Universal CT Representations from Anatomy to Disease Phenotype through Agglomerative Pretraining Com- prehensive language-image pre-training for 3d medical image understanding.arXiv preprint arXiv:2510.15042, 2025a

Reference 14

Resolution: verified exact; arxiv_id, observed 2026-05-25T06:20:24.447345Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation b41f613f-99d6-4936-8a96-5d1aac56e60b · outbound

This paper cites Qwen3 Technical Report.

Universal CT Representations from Anatomy to Disease Phenotype through Agglomerative Pretraining Qwen3 Technical Report

Reference 15

Resolution: verified exact; local_arxiv, observed 2026-05-25T06:20:24.459129Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 26e0c7bd-8622-4a2f-b540-f3a75921e502 · outbound

This paper cites BiomedCLIP: a multimodal biomedical foundation model pretrained from fifteen million scientific image-text pairs.

Universal CT Representations from Anatomy to Disease Phenotype through Agglomerative Pretraining BiomedCLIP: a multimodal biomedical foundation model pretrained from fifteen million scientific image-text pairs

Reference 16

Resolution: verified exact; local_arxiv, observed 2026-05-25T06:20:24.429610Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 4e7b9553-73f3-4ecc-be7e-254d0669b806 · outbound

This paper cites Qwen3 Embedding: Advancing Text Embedding and Reranking Through Foundation Models.

Universal CT Representations from Anatomy to Disease Phenotype through Agglomerative Pretraining Qwen3 Embedding: Advancing Text Embedding and Reranking Through Foundation Models

Reference 17

Resolution: verified exact; local_arxiv, observed 2026-05-25T06:20:24.435415Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 34a1d225-25a5-43d2-a016-95510a46e162 · outbound

This paper cites iBOT: Image BERT Pre-Training with Online Tokenizer.

Universal CT Representations from Anatomy to Disease Phenotype through Agglomerative Pretraining iBOT: Image BERT Pre-Training with Online Tokenizer

Reference 18

Resolution: metadata mismatch; local_arxiv, observed 2026-05-25T06:20:24.441028Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Pith citing papers

Observation cd9d31d4-004a-40ec-afd5-72ebd2e5cb6d · inbound

OrganLens: Organ-Specific Representation Learning for CT Foundation Models cites this paper.

OrganLens: Organ-Specific Representation Learning for CT Foundation Models Universal CT Representations from Anatomy to Disease Phenotype through Agglomerative Pretraining

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-01T03:19:39.259982Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.