Paper Citation Record · LEDGER

Automated Synthesis and Adversarial Validation of Executable Causal Research Pipelines

As of 9 August 2026, this Paper Citation Record lists 18 of 18 outbound references and 0 inbound Pith citation observations for arXiv:2607.21173.

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

pith.paper-citation-record.v1
2607.21173 v1

Coverage vector

measured 18 of 18 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-01T08:16:49.555577Z

measured 18 of 18 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+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

18 of 18 outbound references displayed

verified exact2
verified fuzzy0
unresolved15
parse uncertain0
malformed identifier1
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation b7824616-0559-497c-9fba-9ab7a970f9fc · outbound

This paper cites Cambridge university press, 2009.

Automated Synthesis and Adversarial Validation of Executable Causal Research Pipelines Cambridge university press, 2009

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-01T08:16:47.698888Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 862cbdc3-21ff-4033-87fa-586e4622bf8b · outbound

This paper cites Ice Cream Doesn't Cause Drowning: Benchmarking LLMs Against Statistical Pitfalls in Causal Inference.

Automated Synthesis and Adversarial Validation of Executable Causal Research Pipelines Ice Cream Doesn't Cause Drowning: Benchmarking LLMs Against Statistical Pitfalls in Causal Inference

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-01T08:16:47.777702Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 24b6cd4f-26d2-4b31-8608-33fa091666aa · outbound

This paper cites A systematic literature review on llm-based information retrieval: The issue of contents classification.KDIR, pages 135–146, 2024.

Automated Synthesis and Adversarial Validation of Executable Causal Research Pipelines A systematic literature review on llm-based information retrieval: The issue of contents classification.KDIR, pages 135–146, 2024

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-01T08:16:47.858882Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f85be774-5299-4e73-8d03-6e8f65c8fe4d · outbound

This paper cites The virtual lab of ai agents designs new sars-cov-2 nanobodies.Nature, 646(8085):716–723, 2025.

Automated Synthesis and Adversarial Validation of Executable Causal Research Pipelines The virtual lab of ai agents designs new sars-cov-2 nanobodies.Nature, 646(8085):716–723, 2025

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-01T08:16:47.964998Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e40605c1-aeeb-4faf-9e86-2a80be35e817 · outbound

This paper cites Agent laboratory: Using llm agents as research assistants.Findings of the Association for Computational Linguistics: EMNLP 2025, pages 5977–6043, 2025.

Automated Synthesis and Adversarial Validation of Executable Causal Research Pipelines Agent laboratory: Using llm agents as research assistants.Findings of the Association for Computational Linguistics: EMNLP 2025, pages 5977–6043, 2025

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-01T08:16:48.113774Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9b5b46f5-d4b8-4eed-80ab-f3f5ecf2a302 · outbound

This paper cites Harnessing the power of synthetic data in healthcare: innovation, application, and privacy.NPJ digital medicine, 6(1):186, 2023.

Automated Synthesis and Adversarial Validation of Executable Causal Research Pipelines Harnessing the power of synthetic data in healthcare: innovation, application, and privacy.NPJ digital medicine, 6(1):186, 2023

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-01T08:16:48.224082Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3d8f421a-85c1-4eeb-a101-4e3f75d92b31 · outbound

This paper cites Causal machine learning for predicting treatment outcomes.Nature Medicine, 30(4):958–968, 2024.

Automated Synthesis and Adversarial Validation of Executable Causal Research Pipelines Causal machine learning for predicting treatment outcomes.Nature Medicine, 30(4):958–968, 2024

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-01T08:16:48.319266Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9b224715-1cd0-46dd-8d2e-44ee3eded552 · outbound

This paper cites Target trial emulation: a framework for causal inference from observational data.Jama, 328(24):2446–2447, 2022.

Automated Synthesis and Adversarial Validation of Executable Causal Research Pipelines Target trial emulation: a framework for causal inference from observational data.Jama, 328(24):2446–2447, 2022

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-01T08:16:48.437772Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6b9c58dc-68a8-4bdd-8f84-84ee9461af51 · outbound

This paper cites Causal MAS: A Survey of Large Language Model Architectures for Discovery and Effect Estimation.

Automated Synthesis and Adversarial Validation of Executable Causal Research Pipelines Causal MAS: A Survey of Large Language Model Architectures for Discovery and Effect Estimation

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-01T08:16:48.512809Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3e444cd4-be68-45a1-958a-3bf882fbe4cb · outbound

This paper cites ALCM: Autonomous LLM-Augmented Causal Discovery Framework.

Automated Synthesis and Adversarial Validation of Executable Causal Research Pipelines ALCM: Autonomous LLM-Augmented Causal Discovery Framework

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-01T08:16:48.643295Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 66476e0b-79d9-46ea-b05c-5e0b5f13bcfd · outbound

This paper cites Integrating Large Language Model for Improved Causal Discovery.

Automated Synthesis and Adversarial Validation of Executable Causal Research Pipelines Integrating Large Language Model for Improved Causal Discovery

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-01T08:16:48.717225Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 69e4c3b5-e476-4b54-aa3e-672dda3a43ee · outbound

This paper cites An ai agent for automated causal inference in epidemiology.medRxiv, 2026.

Automated Synthesis and Adversarial Validation of Executable Causal Research Pipelines An ai agent for automated causal inference in epidemiology.medRxiv, 2026

Reference 12

Resolution: verified exact; doi, observed 2026-08-01T08:19:31.537347Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation e2398942-a4bd-4c7a-a955-4e309423d429 · outbound

This paper cites Causal-Copilot: An Autonomous Causal Analysis Agent.

Automated Synthesis and Adversarial Validation of Executable Causal Research Pipelines Causal-Copilot: An Autonomous Causal Analysis Agent

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-01T08:16:48.950420Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8fa44435-6da4-465b-802c-0853b209c248 · outbound

This paper cites Causalagent: A conversational multi-agent system for end-to-end causal inference.arXiv preprint arXiv:2602.11527, 2026.

Automated Synthesis and Adversarial Validation of Executable Causal Research Pipelines Causalagent: A conversational multi-agent system for end-to-end causal inference.arXiv preprint arXiv:2602.11527, 2026

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-01T08:16:49.034063Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c0621942-5962-4844-a2db-9ca3819f28b9 · outbound

This paper cites Causal AI scientist: Facilitating causal data science with large language models.

Automated Synthesis and Adversarial Validation of Executable Causal Research Pipelines Causal AI scientist: Facilitating causal data science with large language models

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-01T08:16:49.091109Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ef2a8334-9423-49a5-84df-ff54985d32d7 · outbound

This paper cites Foundations of structural causal models with cycles and latent variables.The Annals of Statistics, 49(5):2885–2915, 2021.

Automated Synthesis and Adversarial Validation of Executable Causal Research Pipelines Foundations of structural causal models with cycles and latent variables.The Annals of Statistics, 49(5):2885–2915, 2021

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-01T08:16:49.200347Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fc84b712-286e-4977-8c2b-1e0f07c3ede8 · outbound

This paper cites Using natural experiments to evaluate population health and health system interventions: new framework for producers and users of evidence.BMJ, 388, 2025.

Automated Synthesis and Adversarial Validation of Executable Causal Research Pipelines Using natural experiments to evaluate population health and health system interventions: new framework for producers and users of evidence.BMJ, 388, 2025

Reference 17

Resolution: verified exact; doi, observed 2026-08-01T08:19:31.316677Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 7d6d3c02-13bb-4632-a275-86e07daca505 · outbound

This paper cites Causalreasoningbenchmark: A real-world benchmark for disentangled evaluation of causal identification and estimation, 2026.

Automated Synthesis and Adversarial Validation of Executable Causal Research Pipelines Causalreasoningbenchmark: A real-world benchmark for disentangled evaluation of causal identification and estimation, 2026

Reference 18

Resolution: malformed identifier; no resolver link, observed 2026-08-01T08:16:49.555577Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.