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Paper Citation Record · LEDGER

Self-Supervised Representation Learning for Longitudinal Polypharmacy Patterns

As of 11 August 2026, this Paper Citation Record lists 34 of 34 outbound references and 0 inbound Pith citation observations for arXiv:2608.06743.

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

pith.paper-citation-record.v1
2608.06743 v1

Coverage vector

measured 34 of 34 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T21:32:39.859170Z

measured 34 of 34 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-11T06:34:44.6726+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

34 of 34 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 27a86c82-8866-4c0c-b983-a4f4afd2f4c2 · outbound

This paper cites Polypharmacy, hospitalization, and mortality risk: a nationwide cohort study.Scientific Reports, 10(1): 18964, 2020.

Self-Supervised Representation Learning for Longitudinal Polypharmacy Patterns Polypharmacy, hospitalization, and mortality risk: a nationwide cohort study.Scientific Reports, 10(1): 18964, 2020

Reference 1

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Observation a95f66f1-ec44-4c5c-8e86-577134fb2fd5 · outbound

This paper cites Prevalence and factors associ- ated with polypharmacy: a systematic review and meta-analysis.BMC Geriatrics, 22(1): 601, 2022.

Self-Supervised Representation Learning for Longitudinal Polypharmacy Patterns Prevalence and factors associ- ated with polypharmacy: a systematic review and meta-analysis.BMC Geriatrics, 22(1): 601, 2022

Reference 2

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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Observation b1dbc4fb-8313-45ed-8a30-291231c7a126 · outbound

This paper cites an unresolved cited work.

Self-Supervised Representation Learning for Longitudinal Polypharmacy Patterns Unresolved cited work

Reference 3

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Observation f63791ca-e39e-440d-a9a1-12fa58e1e959 · outbound

This paper cites Comparison of overall and comorbidity-free life expectancy between insured adults with and without HIV infection, 2000-2016.JAMA Network Open, 3(6):e207954, 2020.

Self-Supervised Representation Learning for Longitudinal Polypharmacy Patterns Comparison of overall and comorbidity-free life expectancy between insured adults with and without HIV infection, 2000-2016.JAMA Network Open, 3(6):e207954, 2020

Reference 4

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Source-reported events for the cited work

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Observation 99a15646-b911-4e57-8ba4-107dc921cd0c · outbound

This paper cites Non- AIDS-defining comorbidities impact health related quality of life among older adults living with HIV.Frontiers in Medicine, 11:1380731, 2024.

Self-Supervised Representation Learning for Longitudinal Polypharmacy Patterns Non- AIDS-defining comorbidities impact health related quality of life among older adults living with HIV.Frontiers in Medicine, 11:1380731, 2024

Reference 5

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Observation df627d25-21d5-4ad2-a323-af11bf0b7761 · outbound

This paper cites Degree of polypharmacy and cognitive function in older women with HIV.AIDS Research and Human Retroviruses, 38(7):571–579, 2022.

Self-Supervised Representation Learning for Longitudinal Polypharmacy Patterns Degree of polypharmacy and cognitive function in older women with HIV.AIDS Research and Human Retroviruses, 38(7):571–579, 2022

Reference 6

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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Observation 10e13454-33ff-4d4f-8bbc-05fbfb8ae2bc · outbound

This paper cites Anatomical therapeutic chemical classification system (ATC).

Self-Supervised Representation Learning for Longitudinal Polypharmacy Patterns Anatomical therapeutic chemical classification system (ATC)

Reference 7

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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Observation 8b779b73-e806-4ee8-b73a-80c0a31f174e · outbound

This paper cites Group- based multi-trajectory modeling.Statistical Methods in Medical Research, 27(7):2015– 2023, 2018.

Self-Supervised Representation Learning for Longitudinal Polypharmacy Patterns Group- based multi-trajectory modeling.Statistical Methods in Medical Research, 27(7):2015– 2023, 2018

Reference 8

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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Observation daef2049-8220-44af-9243-cfc8f8f9d05c · outbound

This paper cites A latent class mixed model for analysing biomarker trajectories with irregularly scheduled observations.Statistics in Medicine, 19(10):1303–1318, 2000.

Self-Supervised Representation Learning for Longitudinal Polypharmacy Patterns A latent class mixed model for analysing biomarker trajectories with irregularly scheduled observations.Statistics in Medicine, 19(10):1303–1318, 2000

Reference 9

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Source-reported events for the cited work

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Observation 98d0598e-93e6-4f9c-8696-7cb73614f850 · outbound

This paper cites Dynamic programming algorithm optimization for spoken word recognition.IEEE Transactions on Acoustics, Speech, and Signal Processing, 26(1): 43–49, 2003.

Self-Supervised Representation Learning for Longitudinal Polypharmacy Patterns Dynamic programming algorithm optimization for spoken word recognition.IEEE Transactions on Acoustics, Speech, and Signal Processing, 26(1): 43–49, 2003

Reference 10

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Source-reported events for the cited work

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Observation ff5effef-73cf-4ba1-972a-22d68006ab05 · outbound

This paper cites Bayesian analysis for mixture of latent variable hidden Markov models with multivariate longitudinal data.Computational Statistics & Data Analysis, 132:190–211, 2019.

Self-Supervised Representation Learning for Longitudinal Polypharmacy Patterns Bayesian analysis for mixture of latent variable hidden Markov models with multivariate longitudinal data.Computational Statistics & Data Analysis, 132:190–211, 2019

Reference 11

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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Observation 52ebbc5f-1f25-4f61-81d7-230e24d2b324 · outbound

This paper cites Model-based clustering of high-dimensional longitudi- nal data via regularization.Biometrics, 79(2):761–774, 2023.

Self-Supervised Representation Learning for Longitudinal Polypharmacy Patterns Model-based clustering of high-dimensional longitudi- nal data via regularization.Biometrics, 79(2):761–774, 2023

Reference 12

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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Observation d1534e36-3df7-414d-b42e-e3dbad3fee8c · outbound

This paper cites A sparse factor model for clustering high- dimensional longitudinal data.Statistics in Medicine, 43(19):3633–3648, 2024.

Self-Supervised Representation Learning for Longitudinal Polypharmacy Patterns A sparse factor model for clustering high- dimensional longitudinal data.Statistics in Medicine, 43(19):3633–3648, 2024

Reference 13

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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Observation 677bc268-33d9-458c-9c32-9f19f5ac229c · outbound

This paper cites Longitudinal self-supervised learning.Medical Image Analysis, 71:102051, 2021.

Self-Supervised Representation Learning for Longitudinal Polypharmacy Patterns Longitudinal self-supervised learning.Medical Image Analysis, 71:102051, 2021

Reference 14

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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Observation a0970fc0-c845-4580-ab7a-ab1c6e09fb5f · outbound

This paper cites Deep representation learning for clustering longitudinal survival data from electronic health records.Nature Communications, 16(1):2534, 2025.

Self-Supervised Representation Learning for Longitudinal Polypharmacy Patterns Deep representation learning for clustering longitudinal survival data from electronic health records.Nature Communications, 16(1):2534, 2025

Reference 15

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Observation 34a14396-b842-4c83-8294-69a03fab4064 · outbound

This paper cites Self-Supervised Learning with Gaussian Processes.

Self-Supervised Representation Learning for Longitudinal Polypharmacy Patterns Self-Supervised Learning with Gaussian Processes

Reference 16

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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Observation 8cf1e520-696d-4f28-a971-aff1bb5bd53b · outbound

This paper cites an unresolved cited work.

Self-Supervised Representation Learning for Longitudinal Polypharmacy Patterns Unresolved cited work

Reference 17

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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Observation 6f9d8147-9ef1-4d54-ae39-4e7a03a74932 · outbound

This paper cites The National NeuroAIDS Tissue Consortium: a new paradigm in brain banking with an emphasis on infectious disease.Neuropathology and Applied Neurobiology, 27(4):326–335, 2001.

Self-Supervised Representation Learning for Longitudinal Polypharmacy Patterns The National NeuroAIDS Tissue Consortium: a new paradigm in brain banking with an emphasis on infectious disease.Neuropathology and Applied Neurobiology, 27(4):326–335, 2001

Reference 18

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Observation bb008d11-56b0-43a9-a426-0750da956b89 · outbound

This paper cites Welcome to the HNRP.https://hnrp.

Self-Supervised Representation Learning for Longitudinal Polypharmacy Patterns Welcome to the HNRP.https://hnrp

Reference 19

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No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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Observation be81156c-6f33-4a79-acfe-18ff15c007d2 · outbound

This paper cites Kapusnik-Uner, Thang Nguyen, and Olivier Bodenreider.

Self-Supervised Representation Learning for Longitudinal Polypharmacy Patterns Kapusnik-Uner, Thang Nguyen, and Olivier Bodenreider

Reference 20

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Observation bfd1402a-15cd-4dc6-95a8-e6374a73a762 · outbound

This paper cites RxNorm: prescription for electronic drug information exchange.IT Professional, 7(5):17–23, 2005.

Self-Supervised Representation Learning for Longitudinal Polypharmacy Patterns RxNorm: prescription for electronic drug information exchange.IT Professional, 7(5):17–23, 2005

Reference 21

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Observation cdfc9a78-dde4-4e75-8409-0b0596af6012 · outbound

This paper cites ATC.WHO Drug Information, 31(4):629–634, 2017.

Self-Supervised Representation Learning for Longitudinal Polypharmacy Patterns ATC.WHO Drug Information, 31(4):629–634, 2017

Reference 22

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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Observation 7ab920f5-2884-4d06-bd55-221ad3745e52 · outbound

This paper cites National Library of Medicine.

Self-Supervised Representation Learning for Longitudinal Polypharmacy Patterns National Library of Medicine

Reference 23

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No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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Observation cb4a9b26-d53f-4b33-886b-f216a2cdc52c · outbound

This paper cites Selective serotonin reuptake inhibitors.

Self-Supervised Representation Learning for Longitudinal Polypharmacy Patterns Selective serotonin reuptake inhibitors

Reference 24

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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Observation 7ebefe82-8b25-4d77-ac32-6e5b77ffa7b7 · outbound

This paper cites Pratt, Mhairi Kerr, John D.

Self-Supervised Representation Learning for Longitudinal Polypharmacy Patterns Pratt, Mhairi Kerr, John D

Reference 25

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verified exact
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Source-reported events for the cited work

correction dated 2025-10-23. Source: crossref record 10.1136/bmjopen-2017-021122eoc->10.1136/bmjopen-2017-021122:correction, observed 2026-07-11T03:03:07.894922+00:00. This notice travels one citation hop only.

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Observation 44a358c2-1f46-45ca-951f-1dfe34696662 · outbound

This paper cites Validity of the Updated Rx-Risk Index as a Disease Identification and Risk-Adjustment Tool for Use in Observational Health Studies.Clinical Interventions in Aging, 20:309–323, 2025.

Self-Supervised Representation Learning for Longitudinal Polypharmacy Patterns Validity of the Updated Rx-Risk Index as a Disease Identification and Risk-Adjustment Tool for Use in Observational Health Studies.Clinical Interventions in Aging, 20:309–323, 2025

Reference 26

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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Observation 319ae1a1-5d92-4156-b7c4-fa2745bd3481 · outbound

This paper cites A general framework for updating belief distributions.Journal of the Royal Statistical Society Series B: Statistical Methodology, 78(5):1103–1130, 2016.

Self-Supervised Representation Learning for Longitudinal Polypharmacy Patterns A general framework for updating belief distributions.Journal of the Royal Statistical Society Series B: Statistical Methodology, 78(5):1103–1130, 2016

Reference 27

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Source-reported events for the cited work

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Observation 1c78e4e5-5022-40f6-a8bc-da3be99393ab · outbound

This paper cites Generalized Variational Inference: Three arguments for deriving new Posteriors.

Self-Supervised Representation Learning for Longitudinal Polypharmacy Patterns Generalized Variational Inference: Three arguments for deriving new Posteriors

Reference 28

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 10d334b6-b4cd-4d26-adeb-27760970abb3 · outbound

This paper cites Scalable variational Gaussian process classification.

Self-Supervised Representation Learning for Longitudinal Polypharmacy Patterns Scalable variational Gaussian process classification

Reference 29

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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Observation c7e28646-deb8-472f-819e-11a9f48a56f8 · outbound

This paper cites Similarity of neural network representations revisited.

Self-Supervised Representation Learning for Longitudinal Polypharmacy Patterns Similarity of neural network representations revisited

Reference 30

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 55ba5bbc-83bb-41a4-9bc4-8f7cfa3b91d5 · outbound

This paper cites ClusterMLD: An efficient hierarchical cluster- ing method for multivariate longitudinal data.Journal of Computational and Graphical Statistics, 32(3):1131–1144, 2023.

Self-Supervised Representation Learning for Longitudinal Polypharmacy Patterns ClusterMLD: An efficient hierarchical cluster- ing method for multivariate longitudinal data.Journal of Computational and Graphical Statistics, 32(3):1131–1144, 2023

Reference 31

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Observation e69e09d4-f34c-4d88-a704-4af63f72ad79 · outbound

This paper cites Silhouettes: a graphical aid to the interpretation and validation of cluster analysis.Journal of Computational and Applied Mathematics, 20:53–65, 1987.

Self-Supervised Representation Learning for Longitudinal Polypharmacy Patterns Silhouettes: a graphical aid to the interpretation and validation of cluster analysis.Journal of Computational and Applied Mathematics, 20:53–65, 1987

Reference 32

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unresolved
no resolver link, observed 2026-08-10T21:32:39.849629Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T21:32:39.849629Z digest=sha256:c0a1250c15598fde89675d6e79bf11834b7ca69a6e8c64652ec47b550fcbb5a5

Observation a2b48ecf-c3f8-4660-873a-61390a5314fc · outbound

This paper cites an unresolved cited work.

Self-Supervised Representation Learning for Longitudinal Polypharmacy Patterns Unresolved cited work

Reference 33

Resolution
unresolved
raw_fallback, observed 2026-08-10T21:32:40.127921Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T21:32:39.854446Z digest=sha256:26191d31de913a0e165bc3d5ef9d7faf3e7259245c75bc79259aee0f48abf2c4

Observation 211759a7-62fd-4dca-935f-a4d9c9b8d7ac · outbound

This paper cites Self-Supervised Representation Learning for Longitudinal Polypharmacy Patterns.

Self-Supervised Representation Learning for Longitudinal Polypharmacy Patterns Self-Supervised Representation Learning for Longitudinal Polypharmacy Patterns

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T21:32:40.104571Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T21:32:39.859170Z digest=sha256:54f18702cec445d45a780a967e767ac89bc0a4d582818eab081d1f5287140bec

Pith citing papers

No inbound Pith citation observations are available.