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Paper Citation Record · LEDGER

From Baseline to Follow-Up: Counterfactual Spine DXA Image Synthesis in UK Biobank Using a Causal Hierarchical Variational Autoencoder

As of 23 August 2026, this Paper Citation Record lists 24 of 24 outbound references and 0 inbound Pith citation observations for arXiv:2605.22649.

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

pith.paper-citation-record.v1
2605.22649 v1

Coverage vector

measured 24 of 24 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-05-22T06:25:47.999821Z

measured 24 of 24 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

24 of 24 outbound references displayed

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External citation measurements

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Outbound references

Observation f564a2ef-4218-4dfb-93c3-a6e8c7af8d13 · outbound

This paper cites Burden of disease among older adults in europe—trends in mor- tality and disability, 1990–2019.

From Baseline to Follow-Up: Counterfactual Spine DXA Image Synthesis in UK Biobank Using a Causal Hierarchical Variational Autoencoder Burden of disease among older adults in europe—trends in mor- tality and disability, 1990–2019

Reference 1

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Observation ecf3c3b4-3563-4c0d-a7a7-fb37a175c6df · outbound

This paper cites The UK Biobank imaging enhancement of 100,000 participants: rationale, data collection, management and future directions.

From Baseline to Follow-Up: Counterfactual Spine DXA Image Synthesis in UK Biobank Using a Causal Hierarchical Variational Autoencoder The UK Biobank imaging enhancement of 100,000 participants: rationale, data collection, management and future directions

Reference 2

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Observation d259648f-4f80-40d3-a9c7-594728d4861d · outbound

This paper cites The UK Biobank resource with deep phenotyping and genomic data.

From Baseline to Follow-Up: Counterfactual Spine DXA Image Synthesis in UK Biobank Using a Causal Hierarchical Variational Autoencoder The UK Biobank resource with deep phenotyping and genomic data

Reference 3

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Observation 652ef2c9-d23b-493a-b093-69148d9780c1 · outbound

This paper cites Morphometric X-ray absorptiometry and morphometric radiography of the spine: a comparison of prevalent vertebral deformity identification.

From Baseline to Follow-Up: Counterfactual Spine DXA Image Synthesis in UK Biobank Using a Causal Hierarchical Variational Autoencoder Morphometric X-ray absorptiometry and morphometric radiography of the spine: a comparison of prevalent vertebral deformity identification

Reference 4

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Observation d123d339-7cd0-4027-ad87-62fc7fcd25a4 · outbound

This paper cites Detection of vertebral fractures in DXA VFA images using statistical models of appearance and a semi-automatic segmentation.

From Baseline to Follow-Up: Counterfactual Spine DXA Image Synthesis in UK Biobank Using a Causal Hierarchical Variational Autoencoder Detection of vertebral fractures in DXA VFA images using statistical models of appearance and a semi-automatic segmentation

Reference 5

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Observation 785af6fd-0f88-4e9e-a89d-1071fa8b918f · outbound

This paper cites Vertebral fracture: epidemiology, impact and use of DXA vertebral fracture assessment in fracture liaison services.

From Baseline to Follow-Up: Counterfactual Spine DXA Image Synthesis in UK Biobank Using a Causal Hierarchical Variational Autoencoder Vertebral fracture: epidemiology, impact and use of DXA vertebral fracture assessment in fracture liaison services

Reference 6

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Observation a55748ac-ce80-4d32-8d94-78a4ea675dd2 · outbound

This paper cites Vertebral shape: Automatic measurement with dynamically sequenced active appearance models.

From Baseline to Follow-Up: Counterfactual Spine DXA Image Synthesis in UK Biobank Using a Causal Hierarchical Variational Autoencoder Vertebral shape: Automatic measurement with dynamically sequenced active appearance models

Reference 7

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Observation b9020ca7-b902-4006-9630-8238bb6479d8 · outbound

This paper cites Age-related trends in vertebral dimensions.

From Baseline to Follow-Up: Counterfactual Spine DXA Image Synthesis in UK Biobank Using a Causal Hierarchical Variational Autoencoder Age-related trends in vertebral dimensions

Reference 8

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Observation 53c85313-4ee6-429c-8c57-a8bbb7710ec6 · outbound

This paper cites Definition of normal vertebral morphometry using NHANES II radiographs.

From Baseline to Follow-Up: Counterfactual Spine DXA Image Synthesis in UK Biobank Using a Causal Hierarchical Variational Autoencoder Definition of normal vertebral morphometry using NHANES II radiographs

Reference 9

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This paper cites UK biobank: an open access resource for identifying the causes of a wide range of complex diseases of middle and old age.

From Baseline to Follow-Up: Counterfactual Spine DXA Image Synthesis in UK Biobank Using a Causal Hierarchical Variational Autoencoder UK biobank: an open access resource for identifying the causes of a wide range of complex diseases of middle and old age

Reference 10

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Observation 15b890cd-8e73-4c56-a496-ac48aabb806f · outbound

This paper cites Conditional Diffusion Model for Longitudinal Medical Image Generation.

From Baseline to Follow-Up: Counterfactual Spine DXA Image Synthesis in UK Biobank Using a Causal Hierarchical Variational Autoencoder Conditional Diffusion Model for Longitudinal Medical Image Generation

Reference 11

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Observation 69951e3c-deef-444b-9112-3d461b913fdc · outbound

This paper cites CausalGAN: Learning Causal Implicit Generative Models with Adversarial Training.

From Baseline to Follow-Up: Counterfactual Spine DXA Image Synthesis in UK Biobank Using a Causal Hierarchical Variational Autoencoder CausalGAN: Learning Causal Implicit Generative Models with Adversarial Training

Reference 12

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Observation f198d22a-e45c-468b-b950-cfea5ed49515 · outbound

This paper cites CausalV AE: Disentangled representation learning via neural structural causal mod- els.

From Baseline to Follow-Up: Counterfactual Spine DXA Image Synthesis in UK Biobank Using a Causal Hierarchical Variational Autoencoder CausalV AE: Disentangled representation learning via neural structural causal mod- els

Reference 13

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation 3f1176d2-400b-4e5b-b8e9-85138ee63fc7 · outbound

This paper cites Diffusion Causal Models for Counterfactual Estimation.

From Baseline to Follow-Up: Counterfactual Spine DXA Image Synthesis in UK Biobank Using a Causal Hierarchical Variational Autoencoder Diffusion Causal Models for Counterfactual Estimation

Reference 14

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Observation 370e6bcc-9596-47e3-babe-8e8fa842d956 · outbound

This paper cites Pearl,Causality.

From Baseline to Follow-Up: Counterfactual Spine DXA Image Synthesis in UK Biobank Using a Causal Hierarchical Variational Autoencoder Pearl,Causality

Reference 15

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Observation 8121a18d-73f9-4329-a726-4614751a4872 · outbound

This paper cites Deep structural causal models for tractable counterfactual inference.

From Baseline to Follow-Up: Counterfactual Spine DXA Image Synthesis in UK Biobank Using a Causal Hierarchical Variational Autoencoder Deep structural causal models for tractable counterfactual inference

Reference 16

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Observation f140c220-49d3-4994-9671-6f1fac2c5112 · outbound

This paper cites Unified brain MR- ultrasound synthesis using multi-modal hierarchical representations.

From Baseline to Follow-Up: Counterfactual Spine DXA Image Synthesis in UK Biobank Using a Causal Hierarchical Variational Autoencoder Unified brain MR- ultrasound synthesis using multi-modal hierarchical representations

Reference 17

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Observation d2159efe-8b8c-436f-bcf8-b23b4bff96a4 · outbound

This paper cites NV AE: A deep hierarchical variational autoen- coder.

From Baseline to Follow-Up: Counterfactual Spine DXA Image Synthesis in UK Biobank Using a Causal Hierarchical Variational Autoencoder NV AE: A deep hierarchical variational autoen- coder

Reference 18

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Observation a17ffaa9-63ba-4a5f-8fe9-4f48fc84e2c9 · outbound

This paper cites Order-independent constraint-based causal structure learning.

From Baseline to Follow-Up: Counterfactual Spine DXA Image Synthesis in UK Biobank Using a Causal Hierarchical Variational Autoencoder Order-independent constraint-based causal structure learning

Reference 19

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Observation a6d27ee5-b488-4cdb-bc4a-dfac181f99b5 · outbound

This paper cites Constraint- based causal discovery with mixed data.

From Baseline to Follow-Up: Counterfactual Spine DXA Image Synthesis in UK Biobank Using a Causal Hierarchical Variational Autoencoder Constraint- based causal discovery with mixed data

Reference 20

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Source-reported events for the cited work

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Observation 929a478c-da93-4251-aa48-ea5920861c86 · outbound

This paper cites Controlling the false discovery rate: a practical and powerful approach to multiple testing.

From Baseline to Follow-Up: Counterfactual Spine DXA Image Synthesis in UK Biobank Using a Causal Hierarchical Variational Autoencoder Controlling the false discovery rate: a practical and powerful approach to multiple testing

Reference 21

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation 51358e4f-7976-4a42-bc49-3f4b9861cfcf · outbound

This paper cites Causal Inference and Causal Explanation with Background Knowledge.

From Baseline to Follow-Up: Counterfactual Spine DXA Image Synthesis in UK Biobank Using a Causal Hierarchical Variational Autoencoder Causal Inference and Causal Explanation with Background Knowledge

Reference 22

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Source-reported events for the cited work

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Observation cdbfb95c-4d4f-4b66-a2d0-e5a5c26263c7 · outbound

This paper cites DirectLiNGAM: A direct method for learning a linear non-Gaussian structural equation model.

From Baseline to Follow-Up: Counterfactual Spine DXA Image Synthesis in UK Biobank Using a Causal Hierarchical Variational Autoencoder DirectLiNGAM: A direct method for learning a linear non-Gaussian structural equation model

Reference 23

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verified fuzzy
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Source-reported events for the cited work

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Observation 99f9cf7f-fa64-46f0-8c0d-deab43b50d13 · outbound

This paper cites Ladder variational autoencoders.

From Baseline to Follow-Up: Counterfactual Spine DXA Image Synthesis in UK Biobank Using a Causal Hierarchical Variational Autoencoder Ladder variational autoencoders

Reference 24

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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