Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-04T22:44:49.304804Z
Paper Citation Record · LEDGER
Comparing unsupervised learning methods for local structural identification in colloidal systems
As of 23 August 2026, this Paper Citation Record lists 13 of 13 outbound references and 0 inbound Pith citation observations for arXiv:2509.07186.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-23T06:30:58.430688+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
Reference resolution
13 of 13 outbound references displayed
- verified exact0
- verified fuzzy9
- unresolved2
- parse uncertain0
- malformed identifier1
- metadata mismatch1
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation f5c7e903-1349-442a-93f3-ba49ead982e1 · outbound
This paper cites It achieves this by computing the eigenvectors of the covariance matrix of the input data and projecting each data point onto the leading eigenvectors (prin- cipal components).
Comparing unsupervised learning methods for local structural identification in colloidal systems It achieves this by computing the eigenvectors of the covariance matrix of the input data and projecting each data point onto the leading eigenvectors (prin- cipal components)
Reference 1
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-04T22:44:49.632001Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation f9e1ab2d-1b5b-473f-9341-5341e83d0e8d · outbound
This paper cites an unresolved cited work.
Comparing unsupervised learning methods for local structural identification in colloidal systems Unresolved cited work
Reference 2
- Resolution
- unresolved
- raw_fallback, observed 2026-08-04T22:44:49.614436Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation cd826759-dbfc-4cbe-94f7-3f41447c61cd · outbound
This paper cites At its core, UMAP assumes that the data lies on a low- dimensional Riemannian manifold embedded in a higher- dimensional space.
Comparing unsupervised learning methods for local structural identification in colloidal systems At its core, UMAP assumes that the data lies on a low- dimensional Riemannian manifold embedded in a higher- dimensional space
Reference 3
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-04T22:44:49.597670Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation bb32dc15-1167-46b8-a758-06008c8b87fc · outbound
This paper cites In the second step, a fluorescent shell was grown around the particles, through which the particles could be detected with confocal/STED microscopy.
Comparing unsupervised learning methods for local structural identification in colloidal systems In the second step, a fluorescent shell was grown around the particles, through which the particles could be detected with confocal/STED microscopy
Reference 4
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-04T22:44:49.579765Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation dcaa16b0-6a10-4f34-9889-cdf872cf6331 · outbound
This paper cites The supra- particles were index-matched within 0.002 using a mixture of 82.5 wt% glycerol/water.
Comparing unsupervised learning methods for local structural identification in colloidal systems The supra- particles were index-matched within 0.002 using a mixture of 82.5 wt% glycerol/water
Reference 5
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-04T22:44:49.558206Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 2b430105-6cc4-4167-80f3-63bab1156bad · outbound
This paper cites We first analyze the variance explained by each principal component.
Comparing unsupervised learning methods for local structural identification in colloidal systems We first analyze the variance explained by each principal component
Reference 6
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-04T22:44:49.535028Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation af9d00ec-a874-4ce5-be25-0407edea2a72 · outbound
This paper cites Mo- tivated by the results of the PCA analysis, we design the autoencoder to project the structural descriptors into a two- dimensional latent space.
Comparing unsupervised learning methods for local structural identification in colloidal systems Mo- tivated by the results of the PCA analysis, we design the autoencoder to project the structural descriptors into a two- dimensional latent space
Reference 7
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-04T22:44:49.515033Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation f676ddc0-ce55-43c8-8a26-44e7e60e251d · outbound
This paper cites Based on the PCA analysis, we project the data onto a two-dimensional space.
Comparing unsupervised learning methods for local structural identification in colloidal systems Based on the PCA analysis, we project the data onto a two-dimensional space
Reference 8
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-04T22:44:49.495372Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 03968ad5-1149-4483-a101-749437becaf3 · outbound
This paper cites an unresolved cited work.
Comparing unsupervised learning methods for local structural identification in colloidal systems Unresolved cited work
Reference 9
- Resolution
- malformed identifier
- raw_fallback, observed 2026-08-04T22:44:49.474095Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 9f677d01-47ed-4f63-a293-f791306d169c · outbound
This paper cites The variance explained by each principal component, shown in Fig.11(a), indicates that the first three principal components capture a substantial fraction of the total variance.
Comparing unsupervised learning methods for local structural identification in colloidal systems The variance explained by each principal component, shown in Fig.11(a), indicates that the first three principal components capture a substantial fraction of the total variance
Reference 10
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-04T22:44:49.451405Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 37fe8bce-d2ea-4c5b-8ace-2d20204322dc · outbound
This paper cites an unresolved cited work.
Comparing unsupervised learning methods for local structural identification in colloidal systems Unresolved cited work
Reference 11
- Resolution
- unresolved
- raw_fallback, observed 2026-08-04T22:44:49.431474Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 3b84aa2f-edbf-40ab-be0e-acb10d14d1c2 · outbound
This paper cites The GMM clustering procedure is shown in Fig.
Comparing unsupervised learning methods for local structural identification in colloidal systems The GMM clustering procedure is shown in Fig
Reference 12
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-04T22:44:49.409976Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation bd6dccc4-bf1c-48c1-9eb4-0c6735242734 · outbound
This paper cites Relationship between Structure and Dynamics of an Icosahedral Quasicrystal using Unsupervised Machine Learning.
Comparing unsupervised learning methods for local structural identification in colloidal systems Relationship between Structure and Dynamics of an Icosahedral Quasicrystal using Unsupervised Machine Learning
Reference 13
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-08-04T22:44:49.384376Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Pith citing papers
No inbound Pith citation observations are available.