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Paper Citation Record · LEDGER

Finding the right scale of a network: Efficient identification of causal emergence through spectral clustering

As of 16 August 2026, this Paper Citation Record lists 28 of 28 outbound references and 0 inbound Pith citation observations for arXiv:1908.07565.

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

pith.paper-citation-record.v1
1908.07565 v2

Coverage vector

measured 28 of 28 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-14T12:22:46.746540Z

measured 28 of 28 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+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

28 of 28 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 41907793-26be-4b18-936a-4b4823db1246 · outbound

This paper cites Network Science.

Finding the right scale of a network: Efficient identification of causal emergence through spectral clustering Network Science

Reference 1

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Observation 1ecfa5a3-e528-4743-b4a1-9393b0972b91 · outbound

This paper cites The emergence of informative higher scales in complex networks.

Finding the right scale of a network: Efficient identification of causal emergence through spectral clustering The emergence of informative higher scales in complex networks

Reference 2

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Observation 57c905a7-0d9e-4935-8d00-ff3942d8bfa5 · outbound

This paper cites Beyond reductionism.

Finding the right scale of a network: Efficient identification of causal emergence through spectral clustering Beyond reductionism

Reference 3

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Observation 406005e0-8265-4a50-bde6-ae8d1e3549a5 · outbound

This paper cites Quantifying causal emergence shows that macro can beat micro.

Finding the right scale of a network: Efficient identification of causal emergence through spectral clustering Quantifying causal emergence shows that macro can beat micro

Reference 4

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Observation a6708df7-4be1-45c9-ba7e-550115b6d087 · outbound

This paper cites Can the macro beat the micro? Integrated information across spatiotemporal scales.

Finding the right scale of a network: Efficient identification of causal emergence through spectral clustering Can the macro beat the micro? Integrated information across spatiotemporal scales

Reference 5

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Observation b272a7a6-b6fe-49d9-9ae0-85ad39dff0dc · outbound

This paper cites When the map is better than the territory.

Finding the right scale of a network: Efficient identification of causal emergence through spectral clustering When the map is better than the territory

Reference 6

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Observation 8eba2097-a80c-46b9-a0a1-a9cb4035d44e · outbound

This paper cites OPTICS: Ordering points to identify the clustering structure.

Finding the right scale of a network: Efficient identification of causal emergence through spectral clustering OPTICS: Ordering points to identify the clustering structure

Reference 7

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Observation 6d9677ac-6073-40bf-9ca6-8377952a02b0 · outbound

This paper cites Representing higher-order dependencies in networks.

Finding the right scale of a network: Efficient identification of causal emergence through spectral clustering Representing higher-order dependencies in networks

Reference 8

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Observation 8711ab59-0f06-4ae1-b50f-740074dcb1ce · outbound

This paper cites Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference.

Finding the right scale of a network: Efficient identification of causal emergence through spectral clustering Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference

Reference 9

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Observation 0b567d60-2ee3-418a-8e4e-0bae4c413154 · outbound

This paper cites Laplacian of graphs and algebraic connectivity.

Finding the right scale of a network: Efficient identification of causal emergence through spectral clustering Laplacian of graphs and algebraic connectivity

Reference 10

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Observation 84495c4c-085f-4eb5-8a1a-1a5be7660792 · outbound

This paper cites On the performance of spectral graph partitioning methods.

Finding the right scale of a network: Efficient identification of causal emergence through spectral clustering On the performance of spectral graph partitioning methods

Reference 11

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Observation 4fca42ce-94ff-4336-9956-f1eb17ffe410 · outbound

This paper cites Spectral partitioning works: Planar graphs and finite ele- ment meshes.

Finding the right scale of a network: Efficient identification of causal emergence through spectral clustering Spectral partitioning works: Planar graphs and finite ele- ment meshes

Reference 12

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Observation e16d60ae-a81b-4e31-969c-2744fc511b80 · outbound

This paper cites Spectra of random graphs with given expected degrees.

Finding the right scale of a network: Efficient identification of causal emergence through spectral clustering Spectra of random graphs with given expected degrees

Reference 13

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Finding the right scale of a network: Efficient identification of causal emergence through spectral clustering Spectra of some simple graphs

Reference 14

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Observation 59fe4011-aff8-44f4-99d3-249d4cb7805c · outbound

This paper cites Introduction to Linear Algebra.

Finding the right scale of a network: Efficient identification of causal emergence through spectral clustering Introduction to Linear Algebra

Reference 15

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Observation ed94680e-6d1a-45b7-bf61-211552cc14d0 · outbound

This paper cites An overview of gradient descent optimization algorithms.

Finding the right scale of a network: Efficient identification of causal emergence through spectral clustering An overview of gradient descent optimization algorithms

Reference 16

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Observation 96d17da1-1a43-498f-bf9b-a47a97f13a42 · outbound

This paper cites A method for unconstrained convex minimization problem with the rate of convergence O (1/kˆ 2).

Finding the right scale of a network: Efficient identification of causal emergence through spectral clustering A method for unconstrained convex minimization problem with the rate of convergence O (1/kˆ 2)

Reference 17

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This paper cites Scale-free networks: a decade and beyond.

Finding the right scale of a network: Efficient identification of causal emergence through spectral clustering Scale-free networks: a decade and beyond

Reference 18

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Finding the right scale of a network: Efficient identification of causal emergence through spectral clustering Efficient behavior of small-world networks

Reference 19

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Observation 0302b770-8964-41af-87f6-47cca21c132c · outbound

This paper cites A set of measures of centrality based on betweenness.

Finding the right scale of a network: Efficient identification of causal emergence through spectral clustering A set of measures of centrality based on betweenness

Reference 20

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This paper cites Eigenvector-centrality—a node-centrality?.

Finding the right scale of a network: Efficient identification of causal emergence through spectral clustering Eigenvector-centrality—a node-centrality?

Reference 21

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Finding the right scale of a network: Efficient identification of causal emergence through spectral clustering Communicability in complex networks

Reference 22

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Finding the right scale of a network: Efficient identification of causal emergence through spectral clustering Complex network comparison based on communicability sequence entropy

Reference 23

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Finding the right scale of a network: Efficient identification of causal emergence through spectral clustering Empirical comparison of algorithms for network community detection

Reference 24

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Finding the right scale of a network: Efficient identification of causal emergence through spectral clustering The minicolumn hypothesis in neuroscience

Reference 25

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Finding the right scale of a network: Efficient identification of causal emergence through spectral clustering From the neuron doctrine to neural networks

Reference 26

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Finding the right scale of a network: Efficient identification of causal emergence through spectral clustering Unresolved cited work

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Finding the right scale of a network: Efficient identification of causal emergence through spectral clustering Unresolved cited work

Reference 365

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