Paper Citation Record · LEDGER

Scientists' Perspectives on the Potential for Generative AI in their Fields

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2304.01420.

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

pith.paper-citation-record.v1
2304.01420 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 5 of 5 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T04:06:32.927725Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-23T04:32:32.526180Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 2bac9a2c-a28a-4259-9f9a-3a6ae2aebcd3 · inbound

Position: Multimodal Large Language Models Can Significantly Advance Scientific Reasoning cites this paper.

Position: Multimodal Large Language Models Can Significantly Advance Scientific Reasoning Scientists' Perspectives on the Potential for Generative AI in their Fields

Reference 133

Resolution: verified exact; arxiv_id, observed 2026-05-23T04:32:32.529526Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 947223b6-6d93-4a10-8f48-bbec6031fe73 · inbound

Conversational AI as a Catalyst for Informal Learning: An Empirical Large-Scale Study on LLM Use in Everyday Learning cites this paper.

Conversational AI as a Catalyst for Informal Learning: An Empirical Large-Scale Study on LLM Use in Everyday Learning Scientists' Perspectives on the Potential for Generative AI in their Fields

Reference 55

Resolution: unresolved; no resolver link, observed 2026-08-07T04:06:32.927725Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b22a041e-2e46-44b0-b1a0-8e6b187067b6 · inbound

Synthetic Heuristic Evaluation: A Comparison between AI- and Human-Powered Usability Evaluation cites this paper.

Synthetic Heuristic Evaluation: A Comparison between AI- and Human-Powered Usability Evaluation Scientists' Perspectives on the Potential for Generative AI in their Fields

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-06T20:38:55.941384Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5357ca5c-4c82-45cc-80fe-5151f0dbbb45 · inbound

Omakase: proactive assistance with actionable suggestions for evolving scientific research projects cites this paper.

Omakase: proactive assistance with actionable suggestions for evolving scientific research projects Scientists' Perspectives on the Potential for Generative AI in their Fields

Reference 38

Resolution: verified exact; arxiv_id, observed 2026-05-11T05:21:01.568772Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 2f00473c-edce-4742-b431-88ef1843eabd · inbound

How Researchers Navigate Accountability, Transparency, and Trust When Using AI Tools in Early-Stage Research: A Think-Aloud Study cites this paper.

How Researchers Navigate Accountability, Transparency, and Trust When Using AI Tools in Early-Stage Research: A Think-Aloud Study Scientists' Perspectives on the Potential for Generative AI in their Fields

Reference 49

Resolution: verified exact; arxiv_id, observed 2026-05-11T21:01:12.522251Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.