Paper Citation Record · LEDGER

Revolutionizing Clinical Trials: A Manifesto for AI-Driven Transformation

As of 10 August 2026, this Paper Citation Record lists 30 of 30 outbound references and 1 inbound Pith citation observation for arXiv:2506.09102.

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

pith.paper-citation-record.v1
2506.09102 v1

Coverage vector

measured 30 of 30 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T05:01:51.180547Z

measured 31 of 31 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-19T08:21:05.698812Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-19T08:22:10.832778Z

Reference resolution

30 of 30 outbound references displayed

verified exact2
verified fuzzy19
unresolved8
parse uncertain0
malformed identifier1
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 22350b43-9438-4354-8d1f-41b8aca20601 · outbound

This paper cites Arrhythmia risk stratification of patients after myocardial infarction using personalized heart models.

Revolutionizing Clinical Trials: A Manifesto for AI-Driven Transformation Arrhythmia risk stratification of patients after myocardial infarction using personalized heart models

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:01:56.595819Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 169ca27d-5316-4766-82d8-a69e2f878310 · outbound

This paper cites Estimating treatment effects with causal forests: An application.

Revolutionizing Clinical Trials: A Manifesto for AI-Driven Transformation Estimating treatment effects with causal forests: An application

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:01:56.392504Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation dd973855-97f2-4376-afb3-0988df91bd71 · outbound

This paper cites Causal inference and the data-fusion problem.

Revolutionizing Clinical Trials: A Manifesto for AI-Driven Transformation Causal inference and the data-fusion problem

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-07T05:01:48.555663Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 44753cb7-dd18-4642-bf57-efe9ca6a06ca · outbound

This paper cites From real-world patient data to individualized treatment effects using machine learning: current and future methods to address underlying challenges.

Revolutionizing Clinical Trials: A Manifesto for AI-Driven Transformation From real-world patient data to individualized treatment effects using machine learning: current and future methods to address underlying challenges

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-07T05:01:48.617626Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 536ad652-9485-4796-b024-b4b4f512081d · outbound

This paper cites Automated reverse engineering of nonlinear dynamical systems.

Revolutionizing Clinical Trials: A Manifesto for AI-Driven Transformation Automated reverse engineering of nonlinear dynamical systems

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-07T05:01:48.700547Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 39abedd8-7e2a-4686-abff-b1a9d7e64662 · outbound

This paper cites Interventions to improve recruitment and retention in clinical trials: a survey and workshop to assess current practice and future priorities.

Revolutionizing Clinical Trials: A Manifesto for AI-Driven Transformation Interventions to improve recruitment and retention in clinical trials: a survey and workshop to assess current practice and future priorities

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:01:56.151125Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 9dbbf4f6-7f27-4603-bc7b-66f1e836702e · outbound

This paper cites Discovering governing equations from data by sparse identification of nonlinear dynamical systems.

Revolutionizing Clinical Trials: A Manifesto for AI-Driven Transformation Discovering governing equations from data by sparse identification of nonlinear dynamical systems

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-07T05:01:48.811081Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 32a8483c-41c3-4995-af5f-73f4f7a955cf · outbound

This paper cites Double/Debiased Machine Learning for Treatment and Causal Parameters.

Revolutionizing Clinical Trials: A Manifesto for AI-Driven Transformation Double/Debiased Machine Learning for Treatment and Causal Parameters

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-07T05:01:48.866176Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 61ef666e-cf24-443f-8f19-b9ad7e913430 · outbound

This paper cites Cooper, Thomas F.

Revolutionizing Clinical Trials: A Manifesto for AI-Driven Transformation Cooper, Thomas F

Reference 9

Resolution: verified exact; doi, observed 2026-08-07T05:01:51.593979Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation d661a74b-31f7-4897-854c-c33486c728c7 · outbound

This paper cites Exclusion rates in randomized controlled trials of treatments for physical conditions: a systematic review.

Revolutionizing Clinical Trials: A Manifesto for AI-Driven Transformation Exclusion rates in randomized controlled trials of treatments for physical conditions: a systematic review

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:01:55.883601Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 063e4341-481d-43d6-9901-a5dc57fa3a64 · outbound

This paper cites Automatically learning hybrid digital twins of dynamical systems.

Revolutionizing Clinical Trials: A Manifesto for AI-Driven Transformation Automatically learning hybrid digital twins of dynamical systems

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:01:55.580285Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation e58d60dc-1e09-420c-9385-4ff7e97101ef · outbound

This paper cites ODE discovery for longitudinal heterogeneous treatment effects inference.

Revolutionizing Clinical Trials: A Manifesto for AI-Driven Transformation ODE discovery for longitudinal heterogeneous treatment effects inference

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:01:55.332195Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation acdc3315-52f1-4b19-b109-98e175872b35 · outbound

This paper cites Challenges in recruitment and retention of clinical trial subjects.

Revolutionizing Clinical Trials: A Manifesto for AI-Driven Transformation Challenges in recruitment and retention of clinical trial subjects

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:01:55.161143Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 5c115c71-fee3-408c-99f4-f6fbb6909470 · outbound

This paper cites Med-real2sim: Non-invasive medical digital twins using physics-informed self-supervised learning.

Revolutionizing Clinical Trials: A Manifesto for AI-Driven Transformation Med-real2sim: Non-invasive medical digital twins using physics-informed self-supervised learning

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:01:54.998276Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation f9fe97fa-81d0-44d6-b36a-7e0057c2ceb5 · outbound

This paper cites Using digital twins in viral infection.

Revolutionizing Clinical Trials: A Manifesto for AI-Driven Transformation Using digital twins in viral infection

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:01:54.768791Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 0b45ac56-8626-4eb0-89e2-aa777ab14727 · outbound

This paper cites Neural-ode for pharmacokinetics modeling and its advantage to alternative machine learning models in predicting new dosing regimens.

Revolutionizing Clinical Trials: A Manifesto for AI-Driven Transformation Neural-ode for pharmacokinetics modeling and its advantage to alternative machine learning models in predicting new dosing regimens

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:01:54.589803Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 295c8c7c-147e-4d71-895a-1b37105ef27f · outbound

This paper cites Differences between clinical trials and postmarketing use.

Revolutionizing Clinical Trials: A Manifesto for AI-Driven Transformation Differences between clinical trials and postmarketing use

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:01:54.384239Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 05e80125-3d49-41a9-a940-5dbecf9ff3ad · outbound

This paper cites Estimated costs of pivotal trials for novel therapeutic agents approved by the us food and drug administration, 2015-2016.

Revolutionizing Clinical Trials: A Manifesto for AI-Driven Transformation Estimated costs of pivotal trials for novel therapeutic agents approved by the us food and drug administration, 2015-2016

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:01:54.086903Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 6a2586f5-3c7a-4e11-9e2f-2df5b0be5b24 · outbound

This paper cites Using artificial intelligence & machine learning in the development of drug & biological products: Discussion paper and request for feedback, 2023.

Revolutionizing Clinical Trials: A Manifesto for AI-Driven Transformation Using artificial intelligence & machine learning in the development of drug & biological products: Discussion paper and request for feedback, 2023

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:01:53.896575Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 2e7c2461-1fcf-4d5e-b120-5fca0c58894a · outbound

This paper cites In silico clinical trials: concepts and early adoptions.

Revolutionizing Clinical Trials: A Manifesto for AI-Driven Transformation In silico clinical trials: concepts and early adoptions

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:01:53.644314Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation e6e742b5-4374-4093-9bc2-0960ffe0e75f · outbound

This paper cites Economic evaluation of cost and time required for a platform trial vs conventional trials.

Revolutionizing Clinical Trials: A Manifesto for AI-Driven Transformation Economic evaluation of cost and time required for a platform trial vs conventional trials

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:01:53.317658Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation de3e7e9b-c4ed-46ee-8b0d-131803ac558d · outbound

This paper cites Meta-analysis of chemotherapy in head and neck cancer (mach-nc): An update on 93 randomised trials and 17,346 patients.

Revolutionizing Clinical Trials: A Manifesto for AI-Driven Transformation Meta-analysis of chemotherapy in head and neck cancer (mach-nc): An update on 93 randomised trials and 17,346 patients

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-07T05:01:50.328407Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 82f033b1-06ec-4e7e-9c9f-7d56eefb2ab7 · outbound

This paper cites Synctwin: Treatment effect estimation with longitudinal outcomes.

Revolutionizing Clinical Trials: A Manifesto for AI-Driven Transformation Synctwin: Treatment effect estimation with longitudinal outcomes

Reference 23

Resolution: verified exact; raw_fallback, observed 2026-08-07T05:01:52.016040Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 59ec64ef-6dca-4a8c-85e6-665f1a8c9156 · outbound

This paper cites Ai education for clinicians.

Revolutionizing Clinical Trials: A Manifesto for AI-Driven Transformation Ai education for clinicians

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:01:52.975165Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation c2471f82-d096-4002-9ac7-9d9ea985ae5a · outbound

This paper cites Meta-learners for partially-identified treatment effects across multiple environments.

Revolutionizing Clinical Trials: A Manifesto for AI-Driven Transformation Meta-learners for partially-identified treatment effects across multiple environments

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:01:52.767859Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation e5f81087-1be6-41b8-ab3a-a7e712cc6efc · outbound

This paper cites Costs of drug development and research and development intensity in the us, 2000-2018.

Revolutionizing Clinical Trials: A Manifesto for AI-Driven Transformation Costs of drug development and research and development intensity in the us, 2000-2018

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:01:52.528566Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 03075414-2f7e-4224-9c40-e5b8819f926d · outbound

This paper cites Adapting neural networks for the estimation of treatment effects.

Revolutionizing Clinical Trials: A Manifesto for AI-Driven Transformation Adapting neural networks for the estimation of treatment effects

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-07T05:01:50.873389Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4de3b7d3-a0c5-4e92-ae39-76bd5e4c5f65 · outbound

This paper cites Optimal treatment selection in sequential systemic and locoregional therapy of oropharyngeal squamous carcinomas: deep q-learning with a patient-physician digital twin dyad.

Revolutionizing Clinical Trials: A Manifesto for AI-Driven Transformation Optimal treatment selection in sequential systemic and locoregional therapy of oropharyngeal squamous carcinomas: deep q-learning with a patient-physician digital twin dyad

Reference 28

Resolution: malformed identifier; doi_truncated, observed 2026-08-07T05:01:51.403175Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 461ea0e6-4150-408b-9c66-d8f67d901f60 · outbound

This paper cites Targeted learning: causal inference for observational and experimental data, volume 4.

Revolutionizing Clinical Trials: A Manifesto for AI-Driven Transformation Targeted learning: causal inference for observational and experimental data, volume 4

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-07T05:01:51.097613Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9d531b92-c05c-4eaa-ba4b-063ea701551a · outbound

This paper cites Gpu accelerated digital twins of the human heart open new routes for cardiovascular research.

Revolutionizing Clinical Trials: A Manifesto for AI-Driven Transformation Gpu accelerated digital twins of the human heart open new routes for cardiovascular research

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:01:52.237218Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Pith citing papers

Observation d71af37e-bcd5-41e7-b8b0-b935d3facb44 · inbound

Treatment, evidence, imitation, and chat cites this paper.

Treatment, evidence, imitation, and chat Revolutionizing Clinical Trials: A Manifesto for AI-Driven Transformation

Reference 93

Resolution: verified exact; arxiv_id, observed 2026-05-19T08:22:10.836242Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.