Paper Citation Record · LEDGER

Constraining Nuclear Mass Models Using r-process Observables with Multi-objective Optimization

As of 19 August 2026, this Paper Citation Record lists 35 of 35 outbound references and 0 inbound Pith citation observations for arXiv:2506.06464.

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

pith.paper-citation-record.v1
2506.06464 v1

Coverage vector

measured 35 of 35 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T06:01:05.868129Z

measured 35 of 35 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

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measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

35 of 35 outbound references displayed

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External citation measurements

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Outbound references

Observation 1a4ef3b5-da04-4de9-ae9c-c93823c02282 · outbound

This paper cites , N}, fi(⃗u) ≤ fi(⃗v) (1).

Constraining Nuclear Mass Models Using r-process Observables with Multi-objective Optimization , N}, fi(⃗u) ≤ fi(⃗v) (1)

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T06:01:06.285080Z

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Observation 0e98ffb2-0cc4-4fb8-b639-a5c8be2e2f19 · outbound

This paper cites , N} : fj(⃗u) < fj(⃗v) (2) To apply this method to ML-based mass model selec- tion, each vector represents the predicted masses across the entire nuclear chart.

Constraining Nuclear Mass Models Using r-process Observables with Multi-objective Optimization , N} : fj(⃗u) < fj(⃗v) (2) To apply this method to ML-based mass model selec- tion, each vector represents the predicted masses across the entire nuclear chart

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T06:01:06.276454Z

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Observation 9c2f01ed-0da9-4498-b440-9bfd0965e628 · outbound

This paper cites Aidala, A.

Constraining Nuclear Mass Models Using r-process Observables with Multi-objective Optimization Aidala, A

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T06:01:06.267207Z

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Observation 8739136e-ad66-4ce3-be5f-9ad3cd473902 · outbound

This paper cites Madurga, R.

Constraining Nuclear Mass Models Using r-process Observables with Multi-objective Optimization Madurga, R

Reference 4

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Observation 1680fc44-5597-4d54-9827-e3572170c76e · outbound

This paper cites Lorusso, S.

Constraining Nuclear Mass Models Using r-process Observables with Multi-objective Optimization Lorusso, S

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T06:01:06.249554Z

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Observation a1e1b954-7a23-4688-8ea5-fbe047ef3cc6 · outbound

This paper cites Precision Mass Measurements of 129-131Cd and Their Impact on Stellar Nucleosynthesis via the Rapid Neutron Capture Process.

Constraining Nuclear Mass Models Using r-process Observables with Multi-objective Optimization Precision Mass Measurements of 129-131Cd and Their Impact on Stellar Nucleosynthesis via the Rapid Neutron Capture Process

Reference 6

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Observation c057cc85-5b96-420d-a1a1-3ffa18073e72 · outbound

This paper cites Vilen, J.

Constraining Nuclear Mass Models Using r-process Observables with Multi-objective Optimization Vilen, J

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T06:01:06.240836Z

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Observation 266aa1e2-5ede-4da2-8695-bd5044f2c052 · outbound

This paper cites Lunney, J.

Constraining Nuclear Mass Models Using r-process Observables with Multi-objective Optimization Lunney, J

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T06:01:06.232385Z

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Observation 78f38a25-6cf4-49a3-9349-bc938371369f · outbound

This paper cites Duflo and A.

Constraining Nuclear Mass Models Using r-process Observables with Multi-objective Optimization Duflo and A

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T06:01:06.223770Z

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Observation dca1ec2f-e112-4dd9-b13a-69b820ed0921 · outbound

This paper cites Koura, T.

Constraining Nuclear Mass Models Using r-process Observables with Multi-objective Optimization Koura, T

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T06:01:06.215195Z

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Observation b9c1b647-cfa8-4a9d-80b5-5d36250f0888 · outbound

This paper cites M¨ oller, W.

Constraining Nuclear Mass Models Using r-process Observables with Multi-objective Optimization M¨ oller, W

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T06:01:06.206820Z

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Observation 2ffdf6f8-4b9d-4695-9e32-6dbabfda37b6 · outbound

This paper cites Goriely, N.

Constraining Nuclear Mass Models Using r-process Observables with Multi-objective Optimization Goriely, N

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T06:01:06.198223Z

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This paper cites an unresolved cited work.

Constraining Nuclear Mass Models Using r-process Observables with Multi-objective Optimization Unresolved cited work

Reference 13

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Observation fb5a69a9-ad34-4ee0-9fe6-f6efb812c897 · outbound

This paper cites Machine learning the nuclear mass.

Constraining Nuclear Mass Models Using r-process Observables with Multi-objective Optimization Machine learning the nuclear mass

Reference 14

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Observation e949a1a1-7893-45d8-b8d0-c99b140dd629 · outbound

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Constraining Nuclear Mass Models Using r-process Observables with Multi-objective Optimization Unresolved cited work

Reference 15

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Observation 779ed596-ede4-4e6e-9ef3-08436e124738 · outbound

This paper cites Mumpower, M.

Constraining Nuclear Mass Models Using r-process Observables with Multi-objective Optimization Mumpower, M

Reference 16

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Observation f2572651-17d7-4eaf-92f9-a3813854c6f9 · outbound

This paper cites Y¨ uksel, D.

Constraining Nuclear Mass Models Using r-process Observables with Multi-objective Optimization Y¨ uksel, D

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T06:01:06.170480Z

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Observation c79c22da-62ce-4690-8b81-bf2ab1c9ead3 · outbound

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Constraining Nuclear Mass Models Using r-process Observables with Multi-objective Optimization Unresolved cited work

Reference 19

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Observation c3068302-7e95-47fd-97bf-2f8dbd551620 · outbound

This paper cites Ngatchou, A.

Constraining Nuclear Mass Models Using r-process Observables with Multi-objective Optimization Ngatchou, A

Reference 20

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Observation 00ea01be-5091-44df-abbe-41cb3ca698c3 · outbound

This paper cites Bishop, Mixture density networks, WorkingPaper (As- ton University, 1994).

Constraining Nuclear Mass Models Using r-process Observables with Multi-objective Optimization Bishop, Mixture density networks, WorkingPaper (As- ton University, 1994)

Reference 21

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Constraining Nuclear Mass Models Using r-process Observables with Multi-objective Optimization Unresolved cited work

Reference 22

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Observation bb443b87-2185-4ed3-a1d3-1bf3bd36f386 · outbound

This paper cites Vassh, G.

Constraining Nuclear Mass Models Using r-process Observables with Multi-objective Optimization Vassh, G

Reference 23

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Observation a6422c6f-1ea7-4ce6-b254-41e16c6d9688 · outbound

This paper cites Kajino, W.

Constraining Nuclear Mass Models Using r-process Observables with Multi-objective Optimization Kajino, W

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T06:01:06.107863Z

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Observation f02a0b3e-e4c2-4306-8883-df791ba47609 · outbound

This paper cites Li and B.

Constraining Nuclear Mass Models Using r-process Observables with Multi-objective Optimization Li and B

Reference 25

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Constraining Nuclear Mass Models Using r-process Observables with Multi-objective Optimization Unresolved cited work

Reference 26

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Constraining Nuclear Mass Models Using r-process Observables with Multi-objective Optimization Unresolved cited work

Reference 27

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Observation cf335aaf-38d7-43a5-a9a0-f463a363d3c5 · outbound

This paper cites M¨ oller, M.

Constraining Nuclear Mass Models Using r-process Observables with Multi-objective Optimization M¨ oller, M

Reference 28

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Observation b7b12a17-79bf-4bea-97f8-83e8dbf0b0a0 · outbound

This paper cites Kawano, R.

Constraining Nuclear Mass Models Using r-process Observables with Multi-objective Optimization Kawano, R

Reference 29

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Observation 936b0d65-134e-4502-995a-7db20caf17d3 · outbound

This paper cites Vassh, M.

Constraining Nuclear Mass Models Using r-process Observables with Multi-objective Optimization Vassh, M

Reference 30

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Reference 31

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Constraining Nuclear Mass Models Using r-process Observables with Multi-objective Optimization Unresolved cited work

Reference 32

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Constraining Nuclear Mass Models Using r-process Observables with Multi-objective Optimization Unresolved cited work

Reference 33

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Observation ebad2060-bc98-4a41-a2bb-5c84766d6125 · outbound

This paper cites Californium-254 and kilonova light curves.

Constraining Nuclear Mass Models Using r-process Observables with Multi-objective Optimization Californium-254 and kilonova light curves

Reference 34

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Constraining Nuclear Mass Models Using r-process Observables with Multi-objective Optimization Unresolved cited work

Reference 35

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Observation 7a0dfdbb-497b-4561-a70d-d55d5d3a88fe · outbound

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Constraining Nuclear Mass Models Using r-process Observables with Multi-objective Optimization Unresolved cited work

Reference 36

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Pith citing papers

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