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Paper Citation Record · LEDGER

Quantum Ensembling Methods for Healthcare and Life Science

As of 8 August 2026, this Paper Citation Record lists 39 of 39 outbound references and 0 inbound Pith citation observations for arXiv:2506.02213.

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

pith.paper-citation-record.v1
2506.02213 v1

Coverage vector

measured 39 of 39 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T11:32:23.214322Z

measured 39 of 39 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

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measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

39 of 39 outbound references displayed

  • verified exact1
  • verified fuzzy22
  • unresolved16
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

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Outbound references

Observation 17fef5b1-b88c-4117-a881-221a93b28c23 · outbound

This paper cites Biology and medicine in the landscape of quantum advantages.Journal of the Royal Society Interface, 19(196):20220541, 2022.

Quantum Ensembling Methods for Healthcare and Life Science Biology and medicine in the landscape of quantum advantages.Journal of the Royal Society Interface, 19(196):20220541, 2022

Reference 1

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Observation 90a18287-cb87-427d-8c37-1ace362aa50b · outbound

This paper cites Mapping global dynamics of benchmark cre- ation and saturation in artificial intelligence.Nature Communications, 13(1):6793, 2022.

Quantum Ensembling Methods for Healthcare and Life Science Mapping global dynamics of benchmark cre- ation and saturation in artificial intelligence.Nature Communications, 13(1):6793, 2022

Reference 2

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 42043799-8512-4caf-9581-b376e4d5d898 · outbound

This paper cites an unresolved cited work.

Quantum Ensembling Methods for Healthcare and Life Science Unresolved cited work

Reference 3

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Observation ac479e91-0775-4d72-8817-2f18d84d0566 · outbound

This paper cites Flother, Gad Getz, Mark Goldsmith, Tanvi Gujarati, Aldo Guzman-Saenz, Dimitrios Iliopoulos, Gavin O.

Quantum Ensembling Methods for Healthcare and Life Science Flother, Gad Getz, Mark Goldsmith, Tanvi Gujarati, Aldo Guzman-Saenz, Dimitrios Iliopoulos, Gavin O

Reference 4

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:32:19.467391Z digest=sha256:fb8585ea42c79e9a738d5f13da6bba0a6d5a20ee275a42b7a805785e9aa312e0

Observation e916187b-efe0-4e4b-bedb-3c2a3707a8e2 · outbound

This paper cites Fl ¨other, Daniel Blankenberg, Maria Demidik, Karl Jansen, Raga Krishnakumar, Rajiv Krishnakumar, Nouamane Laanait, Laxmi Parida, Carl Saab, and Filippo Utro.

Quantum Ensembling Methods for Healthcare and Life Science Fl ¨other, Daniel Blankenberg, Maria Demidik, Karl Jansen, Raga Krishnakumar, Rajiv Krishnakumar, Nouamane Laanait, Laxmi Parida, Carl Saab, and Filippo Utro

Reference 5

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Observation 3de6ce7b-a310-4f60-824d-fce12b7725e3 · outbound

This paper cites Quantum computing at the frontiers of biological sciences.Nature Methods, 18, 01 2021.

Quantum Ensembling Methods for Healthcare and Life Science Quantum computing at the frontiers of biological sciences.Nature Methods, 18, 01 2021

Reference 6

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source=pdf_text observed=2026-08-07T11:32:19.650277Z digest=sha256:6aedc282aba8f179783b7fe73ca1787e1689f492c3e5d09664a9a99811c37e9e

Observation 219cf7a0-a9be-4ff1-82a0-6bffe60a06c2 · outbound

This paper cites How can quantum computing be applied in clinical trial design and optimization?Trends Pharmacol.

Quantum Ensembling Methods for Healthcare and Life Science How can quantum computing be applied in clinical trial design and optimization?Trends Pharmacol

Reference 7

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:32:19.769453Z digest=sha256:c3711d66133ec35d0ae1f3d2fec4bee8f44039047623ee377173cd9a4994ca34

Observation 8744444a-8e1a-4223-a6f5-e878412ff95a · outbound

This paper cites Amin, Evgeny Andriyash, Jason Rolfe, Bohdan Kulchyt- skyy, and Roger Melko.

Quantum Ensembling Methods for Healthcare and Life Science Amin, Evgeny Andriyash, Jason Rolfe, Bohdan Kulchyt- skyy, and Roger Melko

Reference 8

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source=pdf_text observed=2026-08-07T11:32:19.912235Z digest=sha256:6d5cb6e95be9820f582ae336fcbc57063c47bceea36866e4b3e0bc87754bb29c

Observation 1239715c-852e-46c0-aa98-b1ab737bfc2e · outbound

This paper cites Qboost: Large scale classifier training withadiabatic quantum optimization.

Quantum Ensembling Methods for Healthcare and Life Science Qboost: Large scale classifier training withadiabatic quantum optimization

Reference 9

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Observation 1805eed8-0e53-4058-b61c-331a02e5c9a6 · outbound

This paper cites Classification with Quantum Neural Networks on Near Term Processors.

Quantum Ensembling Methods for Healthcare and Life Science Classification with Quantum Neural Networks on Near Term Processors

Reference 10

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source=pdf_text observed=2026-08-07T11:32:20.167968Z digest=sha256:05473a84c138ad682ecdbd4ba2daf9f5a4ba15f851a69f3842a333f6c5d40711

Observation 93ee0118-7d08-4592-88ad-1b1048946c9e · outbound

This paper cites Supervised learning with quantum-enhanced feature spaces.Nature, 567(7747):209, 2019.

Quantum Ensembling Methods for Healthcare and Life Science Supervised learning with quantum-enhanced feature spaces.Nature, 567(7747):209, 2019

Reference 11

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Observation b384d6e7-70bb-4b04-a383-147d85d9b028 · outbound

This paper cites Machine learning of high dimensional data on a noisy quantum processor.npj Quantum Information, 7(1):161, 2021.

Quantum Ensembling Methods for Healthcare and Life Science Machine learning of high dimensional data on a noisy quantum processor.npj Quantum Information, 7(1):161, 2021

Reference 12

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Observation 42f76df6-86d3-4870-8669-ac8cec65f677 · outbound

This paper cites an unresolved cited work.

Quantum Ensembling Methods for Healthcare and Life Science Unresolved cited work

Reference 13

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Observation 10647e10-5bf6-4c4e-9274-a00dd449c0db · outbound

This paper cites The effects of data aggregation in statistical analysis.Geographical Analysis, 8(4):428–438, 1976.

Quantum Ensembling Methods for Healthcare and Life Science The effects of data aggregation in statistical analysis.Geographical Analysis, 8(4):428–438, 1976

Reference 14

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Observation e8e7a4ba-ca8d-4d76-88b6-9bf55d5658e0 · outbound

This paper cites Bagging predictors.Machine learning, 24:123–140, 1996.

Quantum Ensembling Methods for Healthcare and Life Science Bagging predictors.Machine learning, 24:123–140, 1996

Reference 15

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Observation ce5b40c6-554c-4a6f-814a-e42f42c2da59 · outbound

This paper cites Experiments with a new boosting algorithm.

Quantum Ensembling Methods for Healthcare and Life Science Experiments with a new boosting algorithm

Reference 16

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source=pdf_text observed=2026-08-07T11:32:20.894347Z digest=sha256:c376bf47b8728eea4edbc8b7b5d5e9230a1101a363bd9d262cac16859b1e5369

Observation b64d2129-57c4-4ae4-9de0-6513b777416e · outbound

This paper cites Xgboost: A scalable tree boosting system.

Quantum Ensembling Methods for Healthcare and Life Science Xgboost: A scalable tree boosting system

Reference 17

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source=pdf_text observed=2026-08-07T11:32:21.012981Z digest=sha256:7b8aff9203b63ba913cf051d70726768ffd03ce7f674e6c447d53f66bccd49a0

Observation 8dbfddfd-dba3-4a71-bddf-1878e68456d2 · outbound

This paper cites Lightgbm: A highly efficient gradient boosting decision tree.Advances in neural information processing systems, 30, 2017.

Quantum Ensembling Methods for Healthcare and Life Science Lightgbm: A highly efficient gradient boosting decision tree.Advances in neural information processing systems, 30, 2017

Reference 18

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Observation ed6c6775-76e7-41cb-b7ff-ee423f117a6e · outbound

This paper cites Catboost: unbiased boosting with categorical features.Advances in neural information processing systems, 31, 2018.

Quantum Ensembling Methods for Healthcare and Life Science Catboost: unbiased boosting with categorical features.Advances in neural information processing systems, 31, 2018

Reference 19

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Observation b369d589-1fed-41c6-a786-0145a400d9f3 · outbound

This paper cites Circuit-centric quantum classifiers.Physical Review A, 101(3):032308, 2020.

Quantum Ensembling Methods for Healthcare and Life Science Circuit-centric quantum classifiers.Physical Review A, 101(3):032308, 2020

Reference 20

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Observation b0e08ffa-a103-4493-b9a6-c3b6a25eb8da · outbound

This paper cites Effect of data encoding on the expressive power of variational quantum-machine- learning models.Physical Review A, 103(3):032430, 2021.

Quantum Ensembling Methods for Healthcare and Life Science Effect of data encoding on the expressive power of variational quantum-machine- learning models.Physical Review A, 103(3):032430, 2021

Reference 21

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Observation 607af0c2-d6de-4c4b-b7bc-813c78a53169 · outbound

This paper cites Quantum ensembles of quantum classifiers.Scientific reports, 8(1):2772, 2018.

Quantum Ensembling Methods for Healthcare and Life Science Quantum ensembles of quantum classifiers.Scientific reports, 8(1):2772, 2018

Reference 22

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Observation c63041e6-2f74-41aa-a8bd-4404d0c24fbf · outbound

This paper cites On quantum ensembles of quantum classifiers.Quantum Machine Intelligence, 2:1–8, 2020.

Quantum Ensembling Methods for Healthcare and Life Science On quantum ensembles of quantum classifiers.Quantum Machine Intelligence, 2:1–8, 2020

Reference 23

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source=pdf_text observed=2026-08-07T11:32:21.683744Z digest=sha256:3afa2ed8e744b75d41698bb5e0e3c46c1d4eb3c9bb0d765ab2af37d19e6ea80e

Observation d6402bbd-92cb-4d70-824e-f89572ef930c · outbound

This paper cites an unresolved cited work.

Quantum Ensembling Methods for Healthcare and Life Science Unresolved cited work

Reference 24

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Observation b0fb6b40-249d-4021-b688-04daed429a8d · outbound

This paper cites Quantum Ensemble for Classification.

Quantum Ensembling Methods for Healthcare and Life Science Quantum Ensemble for Classification

Reference 25

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local_arxiv, observed 2026-08-07T11:32:23.407032Z

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Observation 464bce29-83ca-4c1f-b31b-5b8c9e2b4d4a · outbound

This paper cites Supervised- learning guarantee for quantum adaboost.Physical Review Applied, 22(5):054001, 2024.

Quantum Ensembling Methods for Healthcare and Life Science Supervised- learning guarantee for quantum adaboost.Physical Review Applied, 22(5):054001, 2024

Reference 26

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Observation eb092f33-85f3-407f-85aa-afdde281ed99 · outbound

This paper cites Quantum fingerprinting.Physical review letters, 87(16):167902, 2001.

Quantum Ensembling Methods for Healthcare and Life Science Quantum fingerprinting.Physical review letters, 87(16):167902, 2001

Reference 27

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Observation b1cb7f13-8cef-4ba6-90ff-6896ece8fd55 · outbound

This paper cites How to generate random matrices from the classical compact groups, 2007.

Quantum Ensembling Methods for Healthcare and Life Science How to generate random matrices from the classical compact groups, 2007

Reference 28

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source=pdf_text observed=2026-08-07T11:32:22.237347Z digest=sha256:b1bede10b3d373b7aa2f0314ff9ed37e1a1a93c725cee6b0fe8ee6b0b8bd07f5

Observation 76040dfa-6584-468d-bfcf-436e75295b82 · outbound

This paper cites Adam: A Method for Stochastic Optimization.

Quantum Ensembling Methods for Healthcare and Life Science Adam: A Method for Stochastic Optimization

Reference 29

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source=pdf_text observed=2026-08-07T11:32:22.303295Z digest=sha256:90174d9fae47cd4b81f8d20c321a89be05e1c1e8607d1f46dcb7df91e63e56f6

Observation 30aa9c84-2caf-4c1b-80da-e614bcb48964 · outbound

This paper cites Evaluating analytic gradients on quantum hardware.

Quantum Ensembling Methods for Healthcare and Life Science Evaluating analytic gradients on quantum hardware

Reference 30

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source=pdf_text observed=2026-08-07T11:32:22.392977Z digest=sha256:adce922880d997793bfed76d8fceeaffaa17bce0a9329aa174ab3bb55350c679

Observation 530cb5fa-68be-490c-83e5-72c3e7c43b3e · outbound

This paper cites A desicion-theoretic generalization of on-line learning and an application to boosting.

Quantum Ensembling Methods for Healthcare and Life Science A desicion-theoretic generalization of on-line learning and an application to boosting

Reference 31

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source=pdf_text observed=2026-08-07T11:32:22.482174Z digest=sha256:6caf24cdc440d40c309c137c378738b0fa646f071f01a16bdd9c4ce66d45ae3a

Observation 15590fbe-d63c-4d21-a498-b7f522903614 · outbound

This paper cites Boost- ing algorithms as gradient descent.Advances in neural information processing systems, 12, 1999.

Quantum Ensembling Methods for Healthcare and Life Science Boost- ing algorithms as gradient descent.Advances in neural information processing systems, 12, 1999

Reference 32

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source=pdf_text observed=2026-08-07T11:32:22.567757Z digest=sha256:5c1e5da30d9d9354232f375b0784cb57855cfa743607c9910af8096fd4f10bfd

Observation 22a249ad-ed7d-409f-a0ac-018efb01b13c · outbound

This paper cites Greedy function approximation: a gradient boosting machine.Annals of statistics, pages 1189–1232, 2001.

Quantum Ensembling Methods for Healthcare and Life Science Greedy function approximation: a gradient boosting machine.Annals of statistics, pages 1189–1232, 2001

Reference 33

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source=pdf_text observed=2026-08-07T11:32:22.650709Z digest=sha256:7072992e8f6ee52944f883cb17b570b7683594c195c28fe7e38507392cc6f30d

Observation f3dc74b8-ff07-4a1e-b5b0-c4239ab10222 · outbound

This paper cites Random forests.Machine learning, 45:5–32, 2001.

Quantum Ensembling Methods for Healthcare and Life Science Random forests.Machine learning, 45:5–32, 2001

Reference 34

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source=pdf_text observed=2026-08-07T11:32:22.762049Z digest=sha256:5fee16d58a60ee2d6428ddb84c5dc2e9694eac0c13ecb28cfb2b2d4f0998f508

Observation 35a776e0-21f1-4c22-88eb-9334f78c2619 · outbound

This paper cites Why do tree- based models still outperform deep learning on typical tabular data? Advances in neural information processing systems, 35:507–520, 2022.

Quantum Ensembling Methods for Healthcare and Life Science Why do tree- based models still outperform deep learning on typical tabular data? Advances in neural information processing systems, 35:507–520, 2022

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:32:24.124181Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:32:22.854539Z digest=sha256:f3ba128882132e9bfd7e1c7a0af18c22a88e9b4da6ce3f38c8d0656d8a2429c1

Observation 992901e5-02ea-4e94-9523-b51246295ebf · outbound

This paper cites Moderated estimation of fold change and dispersion for rna-seq data with deseq2.

Quantum Ensembling Methods for Healthcare and Life Science Moderated estimation of fold change and dispersion for rna-seq data with deseq2

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:32:23.911693Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:32:22.944025Z digest=sha256:f9a9c95e1f75aafbf091817be17ac5028baf302ecdb9ebf79754c119603a3e67

Observation 0a5e90f2-344f-4d2d-92cf-b627b8dde726 · outbound

This paper cites Meta-analysis of tumor-and t cell-intrinsic mechanisms of sensitization to checkpoint inhibition.Cell, 184(3):596–614, 2021.

Quantum Ensembling Methods for Healthcare and Life Science Meta-analysis of tumor-and t cell-intrinsic mechanisms of sensitization to checkpoint inhibition.Cell, 184(3):596–614, 2021

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:32:23.744846Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:32:23.044995Z digest=sha256:2a02e40109f53dc15d9589a8478cdec822d746f33c0af1b25caf4ee99b5c1d89

Observation 1e1f2858-5241-4cb2-91ce-1a706afdb426 · outbound

This paper cites A minimal gene set characterizes til specific for diverse tumor antigens across different cancer types.Nature Communications, 16(1):1070, 2025.

Quantum Ensembling Methods for Healthcare and Life Science A minimal gene set characterizes til specific for diverse tumor antigens across different cancer types.Nature Communications, 16(1):1070, 2025

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:32:23.603377Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:32:23.132417Z digest=sha256:b637d48cd19859e870138bd191ddbed6d9d624d130ce58f517d65d905e00fd28

Observation 06dcf9a7-450a-4cd4-9c23-664fa4aebacb · outbound

This paper cites UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction.

Quantum Ensembling Methods for Healthcare and Life Science UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-07T11:32:23.214322Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:32:23.214322Z digest=sha256:2efcfac35d211b85ab95dcd116c3b0cd9809748c464fb95b37f5b19b69a69363

Pith citing papers

No inbound Pith citation observations are available.