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Paper Citation Record · LEDGER

Using machine learning to inform harvest control rule design in complex fishery settings

As of 13 August 2026, this Paper Citation Record lists 6 of 6 outbound references and 0 inbound Pith citation observations for arXiv:2412.12400.

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

pith.paper-citation-record.v1
2412.12400 v2

Coverage vector

measured 6 of 6 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T14:12:46.764689Z

measured 6 of 6 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-13T06:32:02.005865+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

6 of 6 outbound references displayed

  • verified exact0
  • verified fuzzy4
  • unresolved2
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 3ce4b2ef-82b4-44dd-8523-902d714e02c0 · outbound

This paper cites Magnuson-Stevens Fishery Conservation and Management Act.

Using machine learning to inform harvest control rule design in complex fishery settings Magnuson-Stevens Fishery Conservation and Management Act

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T14:12:46.869859Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-11T14:12:46.740715Z digest=sha256:858b75e36f72522d7290b5a206da680b3b55725e505dbf433a20dd7a09dec6c4

Observation 89b5192d-2ffa-48b8-a4f3-67409c671927 · outbound

This paper cites Optimal fishery policy: An equilibrium solution with irreversible investment.

Using machine learning to inform harvest control rule design in complex fishery settings Optimal fishery policy: An equilibrium solution with irreversible investment

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T14:12:46.843453Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-11T14:12:46.749657Z digest=sha256:7a1fe888a96b23b2faeec58c7f74fabac1366eeba874d350f1d19b6242fc2566

Observation 340a0885-643f-4ad2-89a2-93a777f99e67 · outbound

This paper cites Analysis of the eastern Pacific yellowfin tuna fishery based on multiple management objectives.

Using machine learning to inform harvest control rule design in complex fishery settings Analysis of the eastern Pacific yellowfin tuna fishery based on multiple management objectives

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T14:12:46.827302Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-11T14:12:46.764689Z digest=sha256:f6235193fb62089eff50b555e909345a8b4c37e335eced2acbbd3bd9c2dcdf53

Observation 1c7fadfe-4b4e-48a3-b0e6-50deb8df08ec · outbound

This paper cites A Tutorial on Bayesian Optimization.

Using machine learning to inform harvest control rule design in complex fishery settings A Tutorial on Bayesian Optimization

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-11T14:12:46.754190Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T14:12:46.754190Z digest=sha256:77394c24cd2aa3d71bed47ae60bbd6be6669bbc085727dc22091b2e62c0886ad

Observation 77adb1cd-d81e-4343-b81c-37d606b1a274 · outbound

This paper cites Proximal Policy Optimization Algorithms.

Using machine learning to inform harvest control rule design in complex fishery settings Proximal Policy Optimization Algorithms

Reference 95

Resolution
unresolved
no resolver link, observed 2026-08-11T14:12:46.759670Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T14:12:46.759670Z digest=sha256:e62872a38fd101344351c88015e0f08f9b569c1bade98941b5ec5cbf56bd197c

Observation bf338bf8-7554-49ae-aaf0-26a1e9155771 · outbound

This paper cites Reinforcement learning and optimal control.

Using machine learning to inform harvest control rule design in complex fishery settings Reinforcement learning and optimal control

Reference 265

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T14:12:46.857439Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-11T14:12:46.745338Z digest=sha256:c4dbfb415f1d576fa752cc787d3edf000f74f63e5c1e7e02e7f8669bf2977902

Pith citing papers

No inbound Pith citation observations are available.