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Paper Citation Record · LEDGER

Characterizing Stellar Streams with Error-Aware Machine Learning

As of 14 August 2026, this Paper Citation Record lists 24 of 24 outbound references and 0 inbound Pith citation observations for arXiv:2606.09576.

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

pith.paper-citation-record.v1
2606.09576 v1

Coverage vector

measured 24 of 24 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-07-11T11:50:26.030339Z

measured 24 of 24 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 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

24 of 24 outbound references displayed

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  • verified fuzzy0
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  • malformed identifier2
  • metadata mismatch10

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 85e30928-4046-4e86-a8ec-293ed9971401 · outbound

This paper cites Weighted variation spaces and approximation by shallow ReLU networks.

Characterizing Stellar Streams with Error-Aware Machine Learning Weighted variation spaces and approximation by shallow ReLU networks

Reference 1

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arxiv_id, observed 2026-06-27T16:41:03.818616Z

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.

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Observation 0f908028-5682-4dce-ae9e-7b4bcc4f616b · outbound

This paper cites F., Kalmbach, J.

Characterizing Stellar Streams with Error-Aware Machine Learning F., Kalmbach, J

Reference 2

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doi, observed 2026-06-27T16:41:03.805048Z

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

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Observation 9daea2ec-0485-428c-b9de-81e7a7e8e74e · outbound

This paper cites NICE: Non-linear Independent Components Estimation.

Characterizing Stellar Streams with Error-Aware Machine Learning NICE: Non-linear Independent Components Estimation

Reference 3

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local_arxiv, observed 2026-06-27T16:41:03.807382Z

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

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Observation b044dc3f-704f-41c1-ac06-7896d16f2163 · outbound

This paper cites NICE: Non-linear Independent Components Estimation.

Characterizing Stellar Streams with Error-Aware Machine Learning NICE: Non-linear Independent Components Estimation

Reference 4

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local_arxiv, observed 2026-06-27T16:41:03.814464Z

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Observation 031b57df-8c42-42d4-8a3c-ed13011f7fbd · outbound

This paper cites Neural Spline Flows.

Characterizing Stellar Streams with Error-Aware Machine Learning Neural Spline Flows

Reference 5

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arxiv_id, observed 2026-06-27T16:41:03.803467Z

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Observation 583db6b4-fb17-4079-acdf-65387251ba87 · outbound

This paper cites Summary of the content and survey properties.

Characterizing Stellar Streams with Error-Aware Machine Learning Summary of the content and survey properties

Reference 6

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doi, observed 2026-06-27T16:41:03.812074Z

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

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Observation 272d966d-69e8-4fee-901f-61c226e1a1bf · outbound

This paper cites J., & Dionatos, O.

Characterizing Stellar Streams with Error-Aware Machine Learning J., & Dionatos, O

Reference 7

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doi, observed 2026-06-27T16:41:03.816230Z

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

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Observation a3a2e8b4-9c77-46e8-870e-050dd2c1872f · outbound

This paper cites Via Machinae 3.0: A search for stellar streams in Gaia with the CATHODE algorithm.

Characterizing Stellar Streams with Error-Aware Machine Learning Via Machinae 3.0: A search for stellar streams in Gaia with the CATHODE algorithm

Reference 8

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arxiv_id, observed 2026-07-03T02:17:34.383589Z

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.

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Observation be50b069-b467-4685-a6cd-2d332df195f0 · outbound

This paper cites Via Machinae 3.0: A search for stellar streams in Gaia with the CATHODE algorithm.

Characterizing Stellar Streams with Error-Aware Machine Learning Via Machinae 3.0: A search for stellar streams in Gaia with the CATHODE algorithm

Reference 9

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arxiv_id, observed 2026-06-27T16:41:03.800887Z

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

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Observation 47ed8739-7a07-4352-aeec-fbe4408b2409 · outbound

This paper cites Characterizing the GD-1 Stream with DESI DR2 Data: Thin Stream and Hot Cocoon.

Characterizing Stellar Streams with Error-Aware Machine Learning Characterizing the GD-1 Stream with DESI DR2 Data: Thin Stream and Hot Cocoon

Reference 10

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local_arxiv, observed 2026-07-03T02:17:34.380897Z

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

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Observation e19a8e30-a062-4dbd-b64f-e8256aa89a19 · outbound

This paper cites Characterizing the GD-1 Stream with DESI DR2 Data: Thin Stream and Hot Cocoon.

Characterizing Stellar Streams with Error-Aware Machine Learning Characterizing the GD-1 Stream with DESI DR2 Data: Thin Stream and Hot Cocoon

Reference 11

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local_arxiv, observed 2026-06-27T16:41:03.822542Z

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Observation d4d9466e-e339-43da-bde5-84c1a0170b73 · outbound

This paper cites Diederik P.

Characterizing Stellar Streams with Error-Aware Machine Learning Diederik P

Reference 12

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doi, observed 2026-06-27T16:41:03.820171Z

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

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Observation 33fad3bd-8a16-47d1-b6b4-2bc2db0bf9aa · outbound

This paper cites keywords =.

Characterizing Stellar Streams with Error-Aware Machine Learning keywords =

Reference 13

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doi, observed 2026-06-27T16:41:03.837597Z

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Observation a2444a44-6d9a-449d-9f97-d1b86f3e105d · outbound

This paper cites A new algorithm for detecting stellar streams.

Characterizing Stellar Streams with Error-Aware Machine Learning A new algorithm for detecting stellar streams

Reference 14

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doi, observed 2026-06-27T16:41:03.834484Z

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

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Observation 0aafe6ca-fadf-4ca3-84ec-59efe1c0a325 · outbound

This paper cites 2023, Monthly Notices of the Royal Astronomical Society, 520, 5225–5258, doi: 10.1093/mnras/stad321.

Characterizing Stellar Streams with Error-Aware Machine Learning 2023, Monthly Notices of the Royal Astronomical Society, 520, 5225–5258, doi: 10.1093/mnras/stad321

Reference 15

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doi, observed 2026-06-27T16:41:03.836033Z

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

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Observation cc5f08a2-c869-404c-b50f-8116ad3701f6 · outbound

This paper cites Benjamin Nachman and David Shih.

Characterizing Stellar Streams with Error-Aware Machine Learning Benjamin Nachman and David Shih

Reference 16

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doi, observed 2026-06-27T16:41:03.832921Z

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

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Observation 4133e362-212a-47a5-a176-a00f1f54e1d3 · outbound

This paper cites Nachman, D.

Characterizing Stellar Streams with Error-Aware Machine Learning Nachman, D

Reference 17

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

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Observation 13cba943-7a7d-4e69-a520-423f6abb88cf · outbound

This paper cites Frank Rosenblatt.

Characterizing Stellar Streams with Error-Aware Machine Learning Frank Rosenblatt

Reference 18

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Observation d88bf060-ea73-4041-b073-a62b57bbe3c6 · outbound

This paper cites Maps of Dust IR Emission for Use in Estimation of Reddening and CMBR Foregrounds.

Characterizing Stellar Streams with Error-Aware Machine Learning Maps of Dust IR Emission for Use in Estimation of Reddening and CMBR Foregrounds

Reference 19

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doi, observed 2026-06-27T16:41:03.839524Z

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Observation ad02cfd5-ecfb-41ce-b591-bec757c09d73 · outbound

This paper cites David Shih, Matthew R.

Characterizing Stellar Streams with Error-Aware Machine Learning David Shih, Matthew R

Reference 20

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Observation 19b9ccc5-f25b-44fb-9933-6e0ddfed7221 · outbound

This paper cites doi:10.1093/mnras/stab3372 , eprint =.

Characterizing Stellar Streams with Error-Aware Machine Learning doi:10.1093/mnras/stab3372 , eprint =

Reference 21

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doi, observed 2026-06-27T16:41:03.824188Z

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Observation c223c329-2854-4fa4-bc0c-a1af700f11d1 · outbound

This paper cites Zephyr : Stitching Heterogeneous Training Data with Normalizing Flows for Photometric Redshift Inference.

Characterizing Stellar Streams with Error-Aware Machine Learning Zephyr : Stitching Heterogeneous Training Data with Normalizing Flows for Photometric Redshift Inference

Reference 22

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arxiv_id, observed 2026-07-03T02:17:34.386221Z

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Observation e57abd40-9022-4469-af33-ecaef2e21aae · outbound

This paper cites Zephyr : Stitching Heterogeneous Training Data with Normalizing Flows for Photometric Redshift Inference.

Characterizing Stellar Streams with Error-Aware Machine Learning Zephyr : Stitching Heterogeneous Training Data with Normalizing Flows for Photometric Redshift Inference

Reference 23

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arxiv_id, observed 2026-06-27T16:41:03.826495Z

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Observation 6c06bb4f-dec3-4ee3-92e0-02baa62e628f · outbound

This paper cites A., & Speagle, J.

Characterizing Stellar Streams with Error-Aware Machine Learning A., & Speagle, J

Reference 24

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doi, observed 2026-06-27T16:41:03.828009Z

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

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