Paper Citation Record · LEDGER

When is a System Discoverable from Data? Discovery Requires Chaos

As of 14 August 2026, this Paper Citation Record lists 100 of 168 outbound references and 5 inbound Pith citation observations for arXiv:2511.08860.

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

pith.paper-citation-record.v1
2511.08860 v2

Coverage vector

measured 100 of 168 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-03T22:50:30.950407Z

measured 105 of 105 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-01T15:24:51.678770Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

100 of 168 outbound references displayed

verified exact3
verified fuzzy0
unresolved97
parse uncertain0
malformed identifier0
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External citation measurements

0
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

Observation 81b0a046-96b4-4a0c-b036-22a0b756ddb9 · outbound

This paper cites Nature Machine Intelligence, 7 0 (1): 0 1--1, 2025.

When is a System Discoverable from Data? Discovery Requires Chaos Nature Machine Intelligence, 7 0 (1): 0 1--1, 2025

Reference 1

Resolution: verified exact; doi, observed 2026-08-03T22:53:32.239830Z

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 78b4db2d-e219-4e22-bcdb-11f6384771dd · outbound

This paper cites Learning-informed parameter identification in nonlinear time-dependent pdes.

When is a System Discoverable from Data? Discovery Requires Chaos Learning-informed parameter identification in nonlinear time-dependent pdes

Reference 2

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Observation 71f2930f-ccdf-4b41-9c25-a08c03419aec · outbound

This paper cites Identification of the coefficient in elliptic equations.

When is a System Discoverable from Data? Discovery Requires Chaos Identification of the coefficient in elliptic equations

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-03T22:50:30.586041Z

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Observation 86a0b634-5521-43e0-9836-56799400c48e · outbound

This paper cites Fernando.

When is a System Discoverable from Data? Discovery Requires Chaos Fernando

Reference 4

Resolution: verified exact; doi, observed 2026-08-03T22:53:32.055030Z

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Observation 8dde55c6-7998-4445-bbf0-e59ae47db5ea · outbound

This paper cites An identification problem for an elliptic equation in two variables.

When is a System Discoverable from Data? Discovery Requires Chaos An identification problem for an elliptic equation in two variables

Reference 5

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Observation c5883603-1c58-4e3e-bc9c-69fc610775ff · outbound

This paper cites Three-dimensional flows, volume 1.

When is a System Discoverable from Data? Discovery Requires Chaos Three-dimensional flows, volume 1

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-03T22:50:30.597836Z

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Observation 78bad77b-ceef-4d18-9016-4a210fe13a50 · outbound

This paper cites Invariant physics-informed neural networks for ordinary differential equations.

When is a System Discoverable from Data? Discovery Requires Chaos Invariant physics-informed neural networks for ordinary differential equations

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-03T22:50:30.602525Z

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Observation 37a82eae-40b4-4899-a094-f11d0b6d1353 · outbound

This paper cites O ktem, and Carola-Bibiane Sch \.

When is a System Discoverable from Data? Discovery Requires Chaos O ktem, and Carola-Bibiane Sch \

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-03T22:50:30.606245Z

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Observation c294452b-2962-416a-9924-c735b55cbf1c · outbound

This paper cites Adriano Augusto and Helio J.C.

When is a System Discoverable from Data? Discovery Requires Chaos Adriano Augusto and Helio J.C

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-03T22:50:30.609820Z

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Observation b417d497-9f93-4522-b2c6-b8f2edb5984c · outbound

This paper cites Neural operators for accelerating scientific simulations and design.

When is a System Discoverable from Data? Discovery Requires Chaos Neural operators for accelerating scientific simulations and design

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-03T22:50:30.613627Z

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Observation cbf9596d-289c-43e7-9932-ce23d8179364 · outbound

This paper cites Reproducibility crisis.

When is a System Discoverable from Data? Discovery Requires Chaos Reproducibility crisis

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-03T22:50:30.617169Z

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Observation b7502ad8-d337-43ef-8043-f9b1e2736a28 · outbound

This paper cites Poincar \'e and the Three Body Problem.

When is a System Discoverable from Data? Discovery Requires Chaos Poincar \'e and the Three Body Problem

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-03T22:50:30.620789Z

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Observation 3e109df9-b811-4191-b637-b98848a1a3dc · outbound

This paper cites Representation equivalent neural operators: a framework for alias-free operator learning.

When is a System Discoverable from Data? Discovery Requires Chaos Representation equivalent neural operators: a framework for alias-free operator learning

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-03T22:50:30.624357Z

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Observation fa71ee79-08b9-4b3e-b3e2-15481acd996d · outbound

This paper cites E (3)-equivariant graph neural networks for data-efficient and accurate interatomic potentials.

When is a System Discoverable from Data? Discovery Requires Chaos E (3)-equivariant graph neural networks for data-efficient and accurate interatomic potentials

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-03T22:50:30.627800Z

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Observation 8df720d3-1a23-4a5c-8ed4-8a3f3802a84c · outbound

This paper cites On structural identifiability.

When is a System Discoverable from Data? Discovery Requires Chaos On structural identifiability

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-03T22:50:30.631500Z

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Observation 3bf938b8-f9de-4b09-8db9-99d4fe88fd51 · outbound

This paper cites A survey of projection-based model reduction methods for parametric dynamical systems.

When is a System Discoverable from Data? Discovery Requires Chaos A survey of projection-based model reduction methods for parametric dynamical systems

Reference 16

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Observation 9f3f9986-45c9-4c34-b757-d7ed4d73a5ad · outbound

This paper cites Pangu-Weather: A 3D High-Resolution Model for Fast and Accurate Global Weather Forecast.

When is a System Discoverable from Data? Discovery Requires Chaos Pangu-Weather: A 3D High-Resolution Model for Fast and Accurate Global Weather Forecast

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-03T22:50:30.638884Z

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Observation bd78f33a-cace-4903-97be-0d80426db592 · outbound

This paper cites Neural symbolic regression that scales.

When is a System Discoverable from Data? Discovery Requires Chaos Neural symbolic regression that scales

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-03T22:50:30.643234Z

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Observation 384d1473-52ab-4923-b371-9f4cfeb80b77 · outbound

This paper cites Neural flows: Efficient alternative to neural odes.

When is a System Discoverable from Data? Discovery Requires Chaos Neural flows: Efficient alternative to neural odes

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-03T22:50:30.646758Z

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Observation f81cdd94-fc49-4669-94b7-6539c54fe5f8 · outbound

This paper cites Birkhoff.

When is a System Discoverable from Data? Discovery Requires Chaos Birkhoff

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-03T22:50:30.650328Z

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Observation 1eaeb09d-811b-48df-9b40-2f32a94b978c · outbound

This paper cites Topological chaos: what may this mean ?.

When is a System Discoverable from Data? Discovery Requires Chaos Topological chaos: what may this mean ?

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-03T22:50:30.654147Z

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Observation 6cab51bb-bf63-4ddb-889f-f44ec2fc531a · outbound

This paper cites The control of chaos: theory and applications.

When is a System Discoverable from Data? Discovery Requires Chaos The control of chaos: theory and applications

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-03T22:50:30.657920Z

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Observation a7cc784e-f6de-4c14-9622-fc6262f2e486 · outbound

This paper cites Automated reverse engineering of nonlinear dynamical systems.

When is a System Discoverable from Data? Discovery Requires Chaos Automated reverse engineering of nonlinear dynamical systems

Reference 23

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Observation b4c41809-e9d4-40ab-a8cf-4061c9b6c44f · outbound

This paper cites Deepmod: Deep learning for model discovery in noisy data.

When is a System Discoverable from Data? Discovery Requires Chaos Deepmod: Deep learning for model discovery in noisy data

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-03T22:50:30.665155Z

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Observation 386e9c24-d1a2-446c-bbba-2f459f7c59e6 · outbound

This paper cites Does equivariance matter at scale? In NeurIPS 2024 Workshop on Symmetry and Geometry in Neural Representations, 2025.

When is a System Discoverable from Data? Discovery Requires Chaos Does equivariance matter at scale? In NeurIPS 2024 Workshop on Symmetry and Geometry in Neural Representations, 2025

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-03T22:50:30.668780Z

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Observation da092df6-6639-4efe-8a43-cecf0cd2fc0e · outbound

This paper cites Promising directions of machine learning for partial differential equations.

When is a System Discoverable from Data? Discovery Requires Chaos Promising directions of machine learning for partial differential equations

Reference 26

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Observation 84793805-6dee-450a-87d0-14cea9b688d1 · outbound

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

When is a System Discoverable from Data? Discovery Requires Chaos Discovering governing equations from data by sparse identification of nonlinear dynamical systems

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-03T22:50:30.676191Z

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Observation 6417119b-2add-4e72-a4d1-1d8a72be895a · outbound

This paper cites Chaos as an intermittently forced linear system.

When is a System Discoverable from Data? Discovery Requires Chaos Chaos as an intermittently forced linear system

Reference 28

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Observation 9df0dbfb-148c-4f94-bc21-566701ea6c21 · outbound

This paper cites Canonical Bayesian Linear System Identification.

When is a System Discoverable from Data? Discovery Requires Chaos Canonical Bayesian Linear System Identification

Reference 29

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Observation b104aaef-4bcb-4bfa-8a20-9a9ce8381b0d · outbound

This paper cites Symplectic neural flows for modeling and discovery, 2024.

When is a System Discoverable from Data? Discovery Requires Chaos Symplectic neural flows for modeling and discovery, 2024

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-03T22:50:30.687910Z

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Observation 0d7d6576-8e5b-4ad4-a788-704c4de9a013 · outbound

This paper cites Machine learning and the physical sciences.

When is a System Discoverable from Data? Discovery Requires Chaos Machine learning and the physical sciences

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-03T22:50:30.691834Z

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Observation 429b0372-e8e2-482d-8c04-c917586f0f0d · outbound

This paper cites Identifiability Challenges in Sparse Linear Ordinary Differential Equations.

When is a System Discoverable from Data? Discovery Requires Chaos Identifiability Challenges in Sparse Linear Ordinary Differential Equations

Reference 32

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Observation 8dfe65a1-7a1b-4fe2-9564-90214b729895 · outbound

This paper cites Nathan Kutz, and Steven L.

When is a System Discoverable from Data? Discovery Requires Chaos Nathan Kutz, and Steven L

Reference 33

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Observation 393e1e88-690c-467a-a65d-d5d867a172ef · outbound

This paper cites Neural ordinary differential equations.

When is a System Discoverable from Data? Discovery Requires Chaos Neural ordinary differential equations

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-03T22:50:30.703512Z

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Observation 3e739cf2-0d55-44d1-aebf-4c791287379a · outbound

This paper cites The nonequivalence and dimension formula for attractors of lorenz-type systems.

When is a System Discoverable from Data? Discovery Requires Chaos The nonequivalence and dimension formula for attractors of lorenz-type systems

Reference 35

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Observation 38c59e1d-c61d-409a-bd72-97bdac3a8f56 · outbound

This paper cites Physics-informed learning of governing equations from scarce data.

When is a System Discoverable from Data? Discovery Requires Chaos Physics-informed learning of governing equations from scarce data

Reference 36

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Observation 52a554a8-ce52-4b64-8b5e-79fdfe0977e8 · outbound

This paper cites Chesebro, David Hofmann, Vaibhav Dixit, Earl K.

When is a System Discoverable from Data? Discovery Requires Chaos Chesebro, David Hofmann, Vaibhav Dixit, Earl K

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-03T22:50:30.714619Z

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Observation 9a4fb423-9687-412e-9184-be056031d86d · outbound

This paper cites The double scroll family.

When is a System Discoverable from Data? Discovery Requires Chaos The double scroll family

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-03T22:50:30.718491Z

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Observation 21af5e36-38ee-4d14-8c3f-64e8725d6b58 · outbound

This paper cites Parameter and structural identifiability concepts and ambiguities: a critical review and analysis.

When is a System Discoverable from Data? Discovery Requires Chaos Parameter and structural identifiability concepts and ambiguities: a critical review and analysis

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-03T22:50:30.722389Z

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Observation af8fba09-f820-43b1-aa02-9868421c8911 · outbound

This paper cites Combining data and theory for derivable scientific discovery with ai-descartes.

When is a System Discoverable from Data? Discovery Requires Chaos Combining data and theory for derivable scientific discovery with ai-descartes

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-03T22:50:30.726149Z

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Observation cbb62858-d99a-4c9e-a841-1ff06f22cc3d · outbound

This paper cites Evolving scientific discovery by unifying data and background knowledge with ai hilbert.

When is a System Discoverable from Data? Discovery Requires Chaos Evolving scientific discovery by unifying data and background knowledge with ai hilbert

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-03T22:50:30.730015Z

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Observation 3344e397-c897-4c48-8e77-4e38db86f6cc · outbound

This paper cites Interpretable Machine Learning for Science with PySR and SymbolicRegression.jl.

When is a System Discoverable from Data? Discovery Requires Chaos Interpretable Machine Learning for Science with PySR and SymbolicRegression.jl

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-03T22:50:30.733783Z

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Observation 428e1abe-f59e-4261-8a2d-d93441fa1fd4 · outbound

This paper cites Lagrangian Neural Networks.

When is a System Discoverable from Data? Discovery Requires Chaos Lagrangian Neural Networks

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-03T22:50:30.737795Z

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Observation 866dc772-f529-43f0-ac85-411a289ee324 · outbound

This paper cites Learning Symbolic Physics with Graph Networks.

When is a System Discoverable from Data? Discovery Requires Chaos Learning Symbolic Physics with Graph Networks

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-03T22:50:30.741913Z

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Observation b4c716da-3272-4729-af7e-75c3a92a20f9 · outbound

This paper cites Scientific machine learning through physics--informed neural networks: Where we are and what’s next.

When is a System Discoverable from Data? Discovery Requires Chaos Scientific machine learning through physics--informed neural networks: Where we are and what’s next

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-03T22:50:30.746042Z

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Observation 55bc75fa-c3e8-4b92-a9c9-20f545c7add2 · outbound

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When is a System Discoverable from Data? Discovery Requires Chaos Physics and lie symmetry informed gaussian processes

Reference 46

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Observation b94e8ba3-60ca-424b-a15b-e423570d7bc5 · outbound

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When is a System Discoverable from Data? Discovery Requires Chaos Machine learning in drug discovery: a review

Reference 47

Resolution: unresolved; no resolver link, observed 2026-08-03T22:50:30.753477Z

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Observation f8a50749-afb9-45c7-acfe-e4b8af089633 · outbound

This paper cites Physics-informed neural networks for data-driven simulation: Advantages, limitations, and opportunities.

When is a System Discoverable from Data? Discovery Requires Chaos Physics-informed neural networks for data-driven simulation: Advantages, limitations, and opportunities

Reference 48

Resolution: unresolved; no resolver link, observed 2026-08-03T22:50:30.757028Z

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Observation e49cfa9c-3e9c-4ad5-96df-e0375f7be3a1 · outbound

This paper cites Magnetic control of tokamak plasmas through deep reinforcement learning.

When is a System Discoverable from Data? Discovery Requires Chaos Magnetic control of tokamak plasmas through deep reinforcement learning

Reference 49

Resolution: unresolved; no resolver link, observed 2026-08-03T22:50:30.760608Z

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Observation 16dad2be-76a4-4a11-9b68-db921a6c8b14 · outbound

This paper cites On parameter and structural identifiability: Nonunique observability/reconstructibility for identifiable systems, other ambiguities, and new definitions.

When is a System Discoverable from Data? Discovery Requires Chaos On parameter and structural identifiability: Nonunique observability/reconstructibility for identifiable systems, other ambiguities, and new definitions

Reference 50

Resolution: unresolved; no resolver link, observed 2026-08-03T22:50:30.764252Z

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Observation d58683f2-c2b9-4dad-8171-8038232a0d4b · outbound

This paper cites From digital control to digital twins in medicine: A brief review and future perspectives.

When is a System Discoverable from Data? Discovery Requires Chaos From digital control to digital twins in medicine: A brief review and future perspectives

Reference 51

Resolution: unresolved; no resolver link, observed 2026-08-03T22:50:30.767844Z

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Observation 58c82b45-c1e0-46fa-a411-d8bc53cc7586 · outbound

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When is a System Discoverable from Data? Discovery Requires Chaos Ueber diffusion

Reference 52

Resolution: unresolved; no resolver link, observed 2026-08-03T22:50:30.771389Z

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Observation a24aa23a-476a-442a-9817-de2158c2d8a2 · outbound

This paper cites Theorie analytique de la chaleur, par M.

When is a System Discoverable from Data? Discovery Requires Chaos Theorie analytique de la chaleur, par M

Reference 53

Resolution: unresolved; no resolver link, observed 2026-08-03T22:50:30.775012Z

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Observation b4885255-aacb-4410-9833-22ead081d280 · outbound

This paper cites On determining the dimension of chaotic flows.

When is a System Discoverable from Data? Discovery Requires Chaos On determining the dimension of chaotic flows

Reference 54

Resolution: unresolved; no resolver link, observed 2026-08-03T22:50:30.778638Z

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Observation fa46beb2-6b48-42b7-abf7-18481d384419 · outbound

This paper cites Lorenz like flows: exponential decay of correlations for the Poincar\'e map, logarithm law, quantitative recurrence.

When is a System Discoverable from Data? Discovery Requires Chaos Lorenz like flows: exponential decay of correlations for the Poincar\'e map, logarithm law, quantitative recurrence

Reference 55

Resolution: unresolved; no resolver link, observed 2026-08-03T22:50:30.782240Z

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Observation b92b6663-c070-4e4f-ab0b-22b40ec7a9b9 · outbound

This paper cites Plasma surrogate modelling using Fourier neural operators.

When is a System Discoverable from Data? Discovery Requires Chaos Plasma surrogate modelling using Fourier neural operators

Reference 56

Resolution: unresolved; no resolver link, observed 2026-08-03T22:50:30.785828Z

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Observation 03022f50-9f57-4514-ac8b-e2bcdeb2933f · outbound

This paper cites Measuring the strangeness of strange attractors.

When is a System Discoverable from Data? Discovery Requires Chaos Measuring the strangeness of strange attractors

Reference 57

Resolution: unresolved; no resolver link, observed 2026-08-03T22:50:30.789363Z

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Observation 656a49de-b137-48fb-8eff-4b10e3b82271 · outbound

This paper cites Symbolic regression with a learned concept library.

When is a System Discoverable from Data? Discovery Requires Chaos Symbolic regression with a learned concept library

Reference 58

Resolution: unresolved; no resolver link, observed 2026-08-03T22:50:30.793028Z

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Observation 4a3164b7-c86b-47d5-9b2f-b56c8532bf24 · outbound

This paper cites Hamiltonian neural networks.

When is a System Discoverable from Data? Discovery Requires Chaos Hamiltonian neural networks

Reference 59

Resolution: unresolved; no resolver link, observed 2026-08-03T22:50:30.796793Z

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Observation 991598d2-2232-435a-89ff-ad87b90f3ee9 · outbound

This paper cites Linear chaos.

When is a System Discoverable from Data? Discovery Requires Chaos Linear chaos

Reference 60

Resolution: unresolved; no resolver link, observed 2026-08-03T22:50:30.800423Z

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Observation 72e2ad1b-58b0-4b1c-b995-40ac60fd2564 · outbound

This paper cites Can physics-informed neural networks beat the finite element method? IMA Journal of Applied Mathematics, 89 0 (1): 0 143--174, 2024.

When is a System Discoverable from Data? Discovery Requires Chaos Can physics-informed neural networks beat the finite element method? IMA Journal of Applied Mathematics, 89 0 (1): 0 143--174, 2024

Reference 61

Resolution: unresolved; no resolver link, observed 2026-08-03T22:50:30.803860Z

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Observation 279aef6b-8270-493e-a25b-f94e52dbc96a · outbound

This paper cites Sur les probl \`e mes aux d \'e riv \'e es partielles et leur signification physique.

When is a System Discoverable from Data? Discovery Requires Chaos Sur les probl \`e mes aux d \'e riv \'e es partielles et leur signification physique

Reference 62

Resolution: unresolved; no resolver link, observed 2026-08-03T22:50:30.807534Z

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Observation f4819e88-3bc2-4c45-9868-d5d4e737856c · outbound

This paper cites Pereira, Robert J.

When is a System Discoverable from Data? Discovery Requires Chaos Pereira, Robert J

Reference 63

Resolution: unresolved; no resolver link, observed 2026-08-03T22:50:30.811458Z

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Observation 9e79f5e4-69a6-4bea-a4bd-9d81d1a087e7 · outbound

This paper cites Robust identifiability for symbolic recovery of differential equations.

When is a System Discoverable from Data? Discovery Requires Chaos Robust identifiability for symbolic recovery of differential equations

Reference 64

Resolution: unresolved; no resolver link, observed 2026-08-03T22:50:30.815520Z

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Observation 24cdafd2-4043-42ad-b04b-d297491a6e21 · outbound

This paper cites Poseidon: Efficient foundation models for pdes.

When is a System Discoverable from Data? Discovery Requires Chaos Poseidon: Efficient foundation models for pdes

Reference 65

Resolution: unresolved; no resolver link, observed 2026-08-03T22:50:30.819453Z

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Observation 73497d02-6cdb-481a-934d-64b02b0841b4 · outbound

This paper cites u r ein-und ausgangsgr \.

When is a System Discoverable from Data? Discovery Requires Chaos u r ein-und ausgangsgr \

Reference 66

Resolution: unresolved; no resolver link, observed 2026-08-03T22:50:30.823323Z

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Observation bff7dbcb-dff2-4688-ac22-da0f6a1a599a · outbound

This paper cites On uniqueness in structured model learning.

When is a System Discoverable from Data? Discovery Requires Chaos On uniqueness in structured model learning

Reference 67

Resolution: unresolved; no resolver link, observed 2026-08-03T22:50:30.826954Z

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Observation b626062a-bd58-4206-be94-6f79e1cb10c7 · outbound

This paper cites Deep generative symbolic regression.

When is a System Discoverable from Data? Discovery Requires Chaos Deep generative symbolic regression

Reference 68

Resolution: unresolved; no resolver link, observed 2026-08-03T22:50:30.830627Z

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Observation 5f06a2a9-b77a-4033-a881-b32af2022ace · outbound

This paper cites Artificial intelligence faces reproducibility crisis, 2018.

When is a System Discoverable from Data? Discovery Requires Chaos Artificial intelligence faces reproducibility crisis, 2018

Reference 69

Resolution: unresolved; no resolver link, observed 2026-08-03T22:50:30.834106Z

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Observation a8ea5a51-3693-4303-bb7d-d1f35994abe9 · outbound

This paper cites Highly accurate protein structure prediction with alphafold.

When is a System Discoverable from Data? Discovery Requires Chaos Highly accurate protein structure prediction with alphafold

Reference 70

Resolution: unresolved; no resolver link, observed 2026-08-03T22:50:30.838055Z

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Observation d3e7ea46-2426-4c43-baee-9ca36869b529 · outbound

This paper cites D- CIPHER : Discovery of closed-form partial differential equations.

When is a System Discoverable from Data? Discovery Requires Chaos D- CIPHER : Discovery of closed-form partial differential equations

Reference 71

Resolution: unresolved; no resolver link, observed 2026-08-03T22:50:30.843945Z

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Observation 954c93fe-b823-437c-82ad-b6a62f7320d0 · outbound

This paper cites Sindy-pi: a robust algorithm for parallel implicit sparse identification of nonlinear dynamics.

When is a System Discoverable from Data? Discovery Requires Chaos Sindy-pi: a robust algorithm for parallel implicit sparse identification of nonlinear dynamics

Reference 72

Resolution: unresolved; no resolver link, observed 2026-08-03T22:50:30.847947Z

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Observation 477d2a84-c8f8-49f4-8625-2c70ef468426 · outbound

This paper cites The experimental multi-arm pendulum on a cart: A benchmark system for chaos, learning, and control.

When is a System Discoverable from Data? Discovery Requires Chaos The experimental multi-arm pendulum on a cart: A benchmark system for chaos, learning, and control

Reference 73

Resolution: unresolved; no resolver link, observed 2026-08-03T22:50:30.851635Z

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Observation 76f0e81f-2da1-4ef3-8f7f-b0a120ae28ad · outbound

This paper cites End-to-end symbolic regression with transformers.

When is a System Discoverable from Data? Discovery Requires Chaos End-to-end symbolic regression with transformers

Reference 74

Resolution: unresolved; no resolver link, observed 2026-08-03T22:50:30.855266Z

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Observation 033f287b-1cd8-4233-99a8-734d6f01df3f · outbound

This paper cites Leakage and the reproducibility crisis in machine-learning-based science.

When is a System Discoverable from Data? Discovery Requires Chaos Leakage and the reproducibility crisis in machine-learning-based science

Reference 75

Resolution: unresolved; no resolver link, observed 2026-08-03T22:50:30.858879Z

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Observation 3b5484d8-3cc4-4cc1-a96a-a8479950945a · outbound

This paper cites Benchmarking sparse system identification with low-dimensional chaos.

When is a System Discoverable from Data? Discovery Requires Chaos Benchmarking sparse system identification with low-dimensional chaos

Reference 76

Resolution: unresolved; no resolver link, observed 2026-08-03T22:50:30.862578Z

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Observation 057d8cad-4904-49f9-b1d9-e465447da8a2 · outbound

This paper cites Benchmarking sparse system identification with low-dimensional chaos.

When is a System Discoverable from Data? Discovery Requires Chaos Benchmarking sparse system identification with low-dimensional chaos

Reference 77

Resolution: unresolved; no resolver link, observed 2026-08-03T22:50:30.866118Z

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Observation 4835fd39-aff1-4313-a10a-852e6c899490 · outbound

This paper cites Machine learning in the search for new fundamental physics.

When is a System Discoverable from Data? Discovery Requires Chaos Machine learning in the search for new fundamental physics

Reference 78

Resolution: unresolved; no resolver link, observed 2026-08-03T22:50:30.869837Z

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Observation add6dfc7-28b0-45b5-b2b7-2dcc4d00b0de · outbound

This paper cites Astronomia nova.

When is a System Discoverable from Data? Discovery Requires Chaos Astronomia nova

Reference 79

Resolution: unresolved; no resolver link, observed 2026-08-03T22:50:30.873470Z

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Observation 2d30b7a8-a518-4c72-b9cb-e75d5e6083c0 · outbound

This paper cites The method of proper orthogonal decomposition for dynamical characterization and order reduction of mechanical systems: an overview.

When is a System Discoverable from Data? Discovery Requires Chaos The method of proper orthogonal decomposition for dynamical characterization and order reduction of mechanical systems: an overview

Reference 80

Resolution: unresolved; no resolver link, observed 2026-08-03T22:50:30.877076Z

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Observation 36b35f60-4fec-426f-8f42-554f8f7e883a · outbound

This paper cites Parameter identification for elliptic problems.

When is a System Discoverable from Data? Discovery Requires Chaos Parameter identification for elliptic problems

Reference 81

Resolution: unresolved; no resolver link, observed 2026-08-03T22:50:30.880532Z

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Observation 97223081-b3eb-43f5-89c7-3d410993a128 · outbound

This paper cites Machine learning--accelerated computational fluid dynamics.

When is a System Discoverable from Data? Discovery Requires Chaos Machine learning--accelerated computational fluid dynamics

Reference 82

Resolution: unresolved; no resolver link, observed 2026-08-03T22:50:30.884281Z

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Observation 8507561b-8b84-415d-85ef-951677594584 · outbound

This paper cites Neural operator: Learning maps between function spaces with applications to pdes.

When is a System Discoverable from Data? Discovery Requires Chaos Neural operator: Learning maps between function spaces with applications to pdes

Reference 83

Resolution: unresolved; no resolver link, observed 2026-08-03T22:50:30.888149Z

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Observation bdf2ef05-fef2-44ad-b5c2-50f7d69a3cf9 · outbound

This paper cites Fourcastnet: Accelerating global high-resolution weather forecasting using adaptive fourier neural operators.

When is a System Discoverable from Data? Discovery Requires Chaos Fourcastnet: Accelerating global high-resolution weather forecasting using adaptive fourier neural operators

Reference 84

Resolution: unresolved; no resolver link, observed 2026-08-03T22:50:30.891859Z

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Observation 838fffc7-28e0-4f83-abb9-7c5592e0e80e · outbound

This paper cites Nathan Kutz.

When is a System Discoverable from Data? Discovery Requires Chaos Nathan Kutz

Reference 85

Resolution: unresolved; no resolver link, observed 2026-08-03T22:50:30.895345Z

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Observation 96106467-185b-4ecf-bab5-dc1ef5d52d89 · outbound

This paper cites Dynamic mode decomposition: data-driven modeling of complex systems.

When is a System Discoverable from Data? Discovery Requires Chaos Dynamic mode decomposition: data-driven modeling of complex systems

Reference 86

Resolution: unresolved; no resolver link, observed 2026-08-03T22:50:30.898953Z

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Observation de7e46fa-5a20-4ebd-8801-74f7f77c0bff · outbound

This paper cites Contemporary symbolic regression methods and their relative performance.

When is a System Discoverable from Data? Discovery Requires Chaos Contemporary symbolic regression methods and their relative performance

Reference 87

Resolution: unresolved; no resolver link, observed 2026-08-03T22:50:30.902771Z

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Observation 8ade85e0-642b-4846-8ebb-3048b8fad189 · outbound

This paper cites La Cava, Patryk Orzechowski, Bogdan Burlacu, Fabr \' cio Olivetti de Fran c a, Marco Virgolin, Ying Jin, Michael Kommenda, and Jason H.

When is a System Discoverable from Data? Discovery Requires Chaos La Cava, Patryk Orzechowski, Bogdan Burlacu, Fabr \' cio Olivetti de Fran c a, Marco Virgolin, Ying Jin, Michael Kommenda, and Jason H

Reference 88

Resolution: unresolved; no resolver link, observed 2026-08-03T22:50:30.906241Z

Source-reported events for the cited work

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Observation 9abd1642-5307-4c5b-be0a-9ac9c1336780 · outbound

This paper cites an unresolved cited work.

When is a System Discoverable from Data? Discovery Requires Chaos Unresolved cited work

Reference 89

Resolution: unresolved; no resolver link, observed 2026-08-03T22:50:30.909807Z

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Observation 520f3b63-bcbb-4660-949b-c0bae07e9e64 · outbound

This paper cites Langley, Gary L.

When is a System Discoverable from Data? Discovery Requires Chaos Langley, Gary L

Reference 90

Resolution: unresolved; no resolver link, observed 2026-08-03T22:50:30.913373Z

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Observation 8ab37d1f-fa3c-4e65-85af-ebd296af0751 · outbound

This paper cites Bayesian inverse problems are usually well-posed.

When is a System Discoverable from Data? Discovery Requires Chaos Bayesian inverse problems are usually well-posed

Reference 91

Resolution: unresolved; no resolver link, observed 2026-08-03T22:50:30.917155Z

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Observation 5fbe9299-205a-4cb6-92e2-4b31d1c07e19 · outbound

This paper cites An example of a compact non-C-analytic real subvariety of ${\mathbb R}^3$.

When is a System Discoverable from Data? Discovery Requires Chaos An example of a compact non-C-analytic real subvariety of ${\mathbb R}^3$

Reference 92

Resolution: unresolved; no resolver link, observed 2026-08-03T22:50:30.920679Z

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Observation 8ff1df6b-c66d-45d6-ad5b-5d442c61f7f3 · outbound

This paper cites an unresolved cited work.

When is a System Discoverable from Data? Discovery Requires Chaos Unresolved cited work

Reference 93

Resolution: verified exact; doi, observed 2026-08-03T22:53:31.805417Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation becfdc13-669a-4022-819b-48edd0edd7a4 · outbound

This paper cites Estimation of Lyapunov dimension for the Chen and Lu systems.

When is a System Discoverable from Data? Discovery Requires Chaos Estimation of Lyapunov dimension for the Chen and Lu systems

Reference 94

Resolution: unresolved; no resolver link, observed 2026-08-03T22:50:30.928259Z

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Observation 6da5a809-d582-48da-ac6e-fe88ec4a530a · outbound

This paper cites Solving Seismic Wave Equations on Variable Velocity Models With Fourier Neural Operator.

When is a System Discoverable from Data? Discovery Requires Chaos Solving Seismic Wave Equations on Variable Velocity Models With Fourier Neural Operator

Reference 95

Resolution: unresolved; no resolver link, observed 2026-08-03T22:50:30.932139Z

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Observation 77236d95-1b3e-4111-846e-0d83317b0df4 · outbound

This paper cites Fourier neural operator for parametric partial differential equations.

When is a System Discoverable from Data? Discovery Requires Chaos Fourier neural operator for parametric partial differential equations

Reference 96

Resolution: unresolved; no resolver link, observed 2026-08-03T22:50:30.935644Z

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Unavailable: canonical work link unavailable.

Observation 70bb5240-aef0-4f0d-b9d4-b7d1250acf33 · outbound

This paper cites A new chaotic attractor coined.

When is a System Discoverable from Data? Discovery Requires Chaos A new chaotic attractor coined

Reference 97

Resolution: unresolved; no resolver link, observed 2026-08-03T22:50:30.939362Z

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Observation adc85b9d-97ce-475e-ac9d-4e5a0ed4c18b · outbound

This paper cites DeepONet : Learning nonlinear operators for identifying differential equations based on the universal approximation theorem of operators.

When is a System Discoverable from Data? Discovery Requires Chaos DeepONet : Learning nonlinear operators for identifying differential equations based on the universal approximation theorem of operators

Reference 98

Resolution: unresolved; no resolver link, observed 2026-08-03T22:50:30.943021Z

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Observation fe079ec4-284e-42eb-bd5a-2df330c2d88b · outbound

This paper cites The lorenz attractor is mixing.

When is a System Discoverable from Data? Discovery Requires Chaos The lorenz attractor is mixing

Reference 99

Resolution: unresolved; no resolver link, observed 2026-08-03T22:50:30.946711Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a7654c0c-526e-43a9-9c41-e4c93f2fe202 · outbound

This paper cites an unresolved cited work.

When is a System Discoverable from Data? Discovery Requires Chaos Unresolved cited work

Reference 100

Resolution: unresolved; no resolver link, observed 2026-08-03T22:50:30.950407Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation d7b1389b-5eab-4f8f-8435-22b34b531e13 · inbound

Symbolic recovery of PDEs from measurement data cites this paper.

Symbolic recovery of PDEs from measurement data When is a System Discoverable from Data? Discovery Requires Chaos

Reference 95

Resolution: verified exact; arxiv_id, observed 2026-07-07T02:15:59.317641Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 2581c0e7-abf7-4c22-860c-d0012bab6107 · inbound

Theory and interpretability of Quantum Extreme Learning Machines: a Pauli-transfer matrix approach cites this paper.

Theory and interpretability of Quantum Extreme Learning Machines: a Pauli-transfer matrix approach When is a System Discoverable from Data? Discovery Requires Chaos

Reference 67

Resolution: verified exact; arxiv_id, observed 2026-07-07T02:15:59.317641Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation d08e54e4-9b9b-4c23-a269-7b0f440fb7cf · inbound

Flow map learning in nonlinear vector autoregressive models: influence of the feature-library structure on the training error cites this paper.

Flow map learning in nonlinear vector autoregressive models: influence of the feature-library structure on the training error When is a System Discoverable from Data? Discovery Requires Chaos

Reference 63

Resolution: verified exact; arxiv_id, observed 2026-07-07T02:15:59.317641Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 91312f1e-e86f-4f35-b7e1-ea0a46713376 · inbound

How Low Can You Go? Active Learning for Sparse Model Discovery in the Ultra-Low-Data Limit cites this paper.

How Low Can You Go? Active Learning for Sparse Model Discovery in the Ultra-Low-Data Limit When is a System Discoverable from Data? Discovery Requires Chaos

Reference 2

Resolution: verified exact; arxiv_id, observed 2026-07-07T02:15:59.317641Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation ef604a45-0a09-49b0-bef9-f7b24be85b95 · inbound

Attractor Geometry Determines the Identifiability Limits of System Discovery cites this paper.

Attractor Geometry Determines the Identifiability Limits of System Discovery When is a System Discoverable from Data? Discovery Requires Chaos

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-01T15:24:51.678770Z

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