Paper Citation Record · LEDGER

Efficient dataset construction using active learning and uncertainty-aware neural networks for plasma turbulent transport surrogate models

As of 15 August 2026, this Paper Citation Record lists 9 of 9 outbound references and 0 inbound Pith citation observations for arXiv:2507.15976.

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

pith.paper-citation-record.v1
2507.15976 v1

Coverage vector

measured 9 of 9 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T15:26:38.504722Z

measured 9 of 9 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+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

9 of 9 outbound references displayed

verified exact0
verified fuzzy6
unresolved3
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation d6229441-55dd-4152-894a-17ff335256a9 · outbound

This paper cites Enhanc- ing predictive capabilities in fusion burning plas- mas through surrogate-based optimization in core transport solvers.

Efficient dataset construction using active learning and uncertainty-aware neural networks for plasma turbulent transport surrogate models Enhanc- ing predictive capabilities in fusion burning plas- mas through surrogate-based optimization in core transport solvers

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-06T15:26:37.462910Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 888e8e17-6339-4306-bdbe-10487dd51f6c · outbound

This paper cites Akaike’s information criterion and recent developments in information complexity.

Efficient dataset construction using active learning and uncertainty-aware neural networks for plasma turbulent transport surrogate models Akaike’s information criterion and recent developments in information complexity

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:26:39.526419Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation e8827c78-47ea-4cf6-bbd0-86fde0ba6bb3 · outbound

This paper cites Development of compact tokamak fusion reactor use cases to inform future transport studies.

Efficient dataset construction using active learning and uncertainty-aware neural networks for plasma turbulent transport surrogate models Development of compact tokamak fusion reactor use cases to inform future transport studies

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:26:38.825511Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 37d4f0d1-19e6-4618-ad2d-ae9c75df04cc · outbound

This paper cites Improving gen- eralization with active learning.

Efficient dataset construction using active learning and uncertainty-aware neural networks for plasma turbulent transport surrogate models Improving gen- eralization with active learning

Reference 634

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:26:39.948848Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation bf930ab0-aeae-48d8-b2e5-5d21b03c9eba · outbound

This paper cites 2, Journal Abbreviation: Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition,.

Efficient dataset construction using active learning and uncertainty-aware neural networks for plasma turbulent transport surrogate models 2, Journal Abbreviation: Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition,

Reference 2004

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:26:39.745119Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 4e25e7ab-722d-4424-b587-a9bf1efa8c03 · outbound

This paper cites Deep Learning in Neural Networks: An Overview.

Efficient dataset construction using active learning and uncertainty-aware neural networks for plasma turbulent transport surrogate models Deep Learning in Neural Networks: An Overview

Reference 2018

Resolution: unresolved; no resolver link, observed 2026-08-06T15:26:37.704978Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7d14da95-5ea3-4619-aedc-39da0b77178c · outbound

This paper cites Latent derivative bayesian last layer networks.

Efficient dataset construction using active learning and uncertainty-aware neural networks for plasma turbulent transport surrogate models Latent derivative bayesian last layer networks

Reference 2019

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:26:39.071058Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 305206ed-ae52-43b8-a886-11951e4f589b · outbound

This paper cites Adam: A Method for Stochastic Optimization.

Efficient dataset construction using active learning and uncertainty-aware neural networks for plasma turbulent transport surrogate models Adam: A Method for Stochastic Optimization

Reference 2020

Resolution: unresolved; no resolver link, observed 2026-08-06T15:26:38.345863Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4b5a79c5-a933-49dd-a7c3-8312e0c03ccb · outbound

This paper cites Addressing deep learning model calibration using evidential neural networks and uncertainty-aware training.

Efficient dataset construction using active learning and uncertainty-aware neural networks for plasma turbulent transport surrogate models Addressing deep learning model calibration using evidential neural networks and uncertainty-aware training

Reference 2021

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:26:39.332549Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Pith citing papers

No inbound Pith citation observations are available.