Paper Citation Record · LEDGER

Incorporating structural uncertainty in causal decision making

As of 8 August 2026, this Paper Citation Record lists 36 of 36 outbound references and 0 inbound Pith citation observations for arXiv:2507.23495.

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

pith.paper-citation-record.v1
2507.23495 v1

Coverage vector

measured 36 of 36 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T10:47:03.457147Z

measured 36 of 36 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+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

36 of 36 outbound references displayed

verified exact0
verified fuzzy27
unresolved9
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 83be0de5-d8c9-4ece-96e5-b8bb178dd629 · outbound

This paper cites Causal inference in statistics, social, and biomedical sciences.

Incorporating structural uncertainty in causal decision making Causal inference in statistics, social, and biomedical sciences

Reference 1

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Observation e139f2ff-3d23-4b83-86b6-7fc9f7810033 · outbound

This paper cites Bayesian regression tree models for causal inference: Regularization, confounding, and heterogeneous effects.

Incorporating structural uncertainty in causal decision making Bayesian regression tree models for causal inference: Regularization, confounding, and heterogeneous effects

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T10:47:04.108526Z

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Observation 5d626e8a-837b-4976-bfc9-95835d8180d3 · outbound

This paper cites Causation, pre- diction, and search.

Incorporating structural uncertainty in causal decision making Causation, pre- diction, and search

Reference 3

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This paper cites Review of causal discov- ery methods based on graphical models.

Incorporating structural uncertainty in causal decision making Review of causal discov- ery methods based on graphical models

Reference 4

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This paper cites Statistical Decision Theory and Bayesian Analysis.

Incorporating structural uncertainty in causal decision making Statistical Decision Theory and Bayesian Analysis

Reference 5

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Observation 6c12362c-49a0-4fea-bfcd-8a3b82d0d093 · outbound

This paper cites The Bayesian Choice: From Decision-Theoretic Foundations to Computational Implementation.

Incorporating structural uncertainty in causal decision making The Bayesian Choice: From Decision-Theoretic Foundations to Computational Implementation

Reference 6

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Observation 34bcbace-f6a9-406c-a003-ce4b22769342 · outbound

This paper cites SidechainNet: An All-Atom Protein Structure Dataset for Machine Learning.

Incorporating structural uncertainty in causal decision making SidechainNet: An All-Atom Protein Structure Dataset for Machine Learning

Reference 7

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Observation 757d662f-43e5-4dc5-b617-038b366a7847 · outbound

This paper cites On the completeness of orientation rules for causal discovery in the presence of latent confounders and selection bias.

Incorporating structural uncertainty in causal decision making On the completeness of orientation rules for causal discovery in the presence of latent confounders and selection bias

Reference 8

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This paper cites Optimal structure identification with greedy search.

Incorporating structural uncertainty in causal decision making Optimal structure identification with greedy search

Reference 9

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Observation 04cfa6de-5d70-4ff8-9893-6762b91d7fab · outbound

This paper cites Learning bayesian networks.

Incorporating structural uncertainty in causal decision making Learning bayesian networks

Reference 10

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Observation b3f804c3-91d6-49ff-9b8d-2d6f3f3b48fd · outbound

This paper cites Nonlinear causal discovery with additive noise models.

Incorporating structural uncertainty in causal decision making Nonlinear causal discovery with additive noise models

Reference 11

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Source-reported events for the cited work

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Observation 353706e0-508a-4c61-b0e5-e1fd621339c6 · outbound

This paper cites Causal infer- ence in statistics: A primer.

Incorporating structural uncertainty in causal decision making Causal infer- ence in statistics: A primer

Reference 12

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Observation c4a78898-2fa3-4c8d-8132-1057588b7f36 · outbound

This paper cites Information-geometric approach to inferring causal directions.

Incorporating structural uncertainty in causal decision making Information-geometric approach to inferring causal directions

Reference 13

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This paper cites Bayesian graphical models for discrete data.

Incorporating structural uncertainty in causal decision making Bayesian graphical models for discrete data

Reference 14

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Incorporating structural uncertainty in causal decision making Unresolved cited work

Reference 15

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Observation fd7e2778-92d1-45ac-b0b0-b6eef8903897 · outbound

This paper cites Bayesian model averaging: A tutorial.

Incorporating structural uncertainty in causal decision making Bayesian model averaging: A tutorial

Reference 16

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Observation d9bb0c93-85e1-45c2-899a-e41dcb61e433 · outbound

This paper cites Bayesian Model Selection in Social Research , vol- ume 25.

Incorporating structural uncertainty in causal decision making Bayesian Model Selection in Social Research , vol- ume 25

Reference 17

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Observation 31206fe5-4f99-4460-8776-6606757fcd99 · outbound

This paper cites Optimal predictive model selection.

Incorporating structural uncertainty in causal decision making Optimal predictive model selection

Reference 18

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Observation af1d9a4d-d2af-4c85-86d2-404995e38be9 · outbound

This paper cites Bayesian adap- tive sampling for variable selection and model averaging.

Incorporating structural uncertainty in causal decision making Bayesian adap- tive sampling for variable selection and model averaging

Reference 19

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This paper cites Rosenbaum.

Incorporating structural uncertainty in causal decision making Rosenbaum

Reference 20

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Observation ada78988-d6e5-4818-8bf8-5b3921fa85e2 · outbound

This paper cites VanderWeele and Peng Ding.

Incorporating structural uncertainty in causal decision making VanderWeele and Peng Ding

Reference 21

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Incorporating structural uncertainty in causal decision making Tchetgen Tchetgen

Reference 22

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Observation 6ea8af99-605b-44a6-b491-ae5495651e89 · outbound

This paper cites Sensitivity analysis under unmeasured confound- ing: bounds on the average causal effect.

Incorporating structural uncertainty in causal decision making Sensitivity analysis under unmeasured confound- ing: bounds on the average causal effect

Reference 23

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Incorporating structural uncertainty in causal decision making Unresolved cited work

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Incorporating structural uncertainty in causal decision making Unresolved cited work

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This paper cites Double/debiased machine learning for treat- ment and structural parameters.

Incorporating structural uncertainty in causal decision making Double/debiased machine learning for treat- ment and structural parameters

Reference 26

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Incorporating structural uncertainty in causal decision making Unresolved cited work

Reference 27

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This paper cites Causal effect estimation under multi- ple candidate causal graphs.

Incorporating structural uncertainty in causal decision making Causal effect estimation under multi- ple candidate causal graphs

Reference 28

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This paper cites Learning causal structure under model uncertainty.

Incorporating structural uncertainty in causal decision making Learning causal structure under model uncertainty

Reference 29

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Incorporating structural uncertainty in causal decision making Unresolved cited work

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This paper cites Dehejia and Sadek Wahba.

Incorporating structural uncertainty in causal decision making Dehejia and Sadek Wahba

Reference 31

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This paper cites Calibrating sensitivity analyses for unmeasured con- founding in observational studies.

Incorporating structural uncertainty in causal decision making Calibrating sensitivity analyses for unmeasured con- founding in observational studies

Reference 32

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This paper cites Doubly robust estimation of heterogeneous causal effects.

Incorporating structural uncertainty in causal decision making Doubly robust estimation of heterogeneous causal effects

Reference 33

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This paper cites Causality: Models, Reasoning, and Inference.

Incorporating structural uncertainty in causal decision making Causality: Models, Reasoning, and Inference

Reference 34

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Incorporating structural uncertainty in causal decision making Causal discovery using regression-based conditional independence tests

Reference 35

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This paper cites An introduction to the boot- strap.

Incorporating structural uncertainty in causal decision making An introduction to the boot- strap

Reference 36

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Pith citing papers

No inbound Pith citation observations are available.