Paper Citation Record · LEDGER

Probing the Stochastic Machine: Engaging with LLMs in Statistics Curricula Through Veridical Data Science

As of 22 August 2026, this Paper Citation Record lists 15 of 15 outbound references and 0 inbound Pith citation observations for arXiv:2606.29754.

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

pith.paper-citation-record.v1
2606.29754 v1

Coverage vector

measured 15 of 15 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-06-30T04:18:40.986797Z

measured 15 of 15 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+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

15 of 15 outbound references displayed

verified exact3
verified fuzzy0
unresolved11
parse uncertain0
malformed identifier1
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation fe309996-199e-4f2e-9872-09d0446e08c5 · outbound

This paper cites The American Statistician , number=.

Probing the Stochastic Machine: Engaging with LLMs in Statistics Curricula Through Veridical Data Science The American Statistician , number=

Reference 1

Resolution: unresolved; no resolver link, observed 2026-06-30T04:18:40.986797Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d89f49e4-b9d3-4a24-b145-84e828cf81ae · outbound

This paper cites , editor =.

Probing the Stochastic Machine: Engaging with LLMs in Statistics Curricula Through Veridical Data Science , editor =

Reference 2

Resolution: unresolved; no resolver link, observed 2026-06-30T04:18:40.986797Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 25290d12-82d0-4272-9f50-6877b06df2c7 · outbound

This paper cites Journal of Statistics and Data Science Education , volume=.

Probing the Stochastic Machine: Engaging with LLMs in Statistics Curricula Through Veridical Data Science Journal of Statistics and Data Science Education , volume=

Reference 3

Resolution: unresolved; no resolver link, observed 2026-06-30T04:18:40.986797Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9d56c2fb-f799-4b2d-896f-2d84e3eeed1d · outbound

This paper cites arXiv preprint arXiv:2508.00835 , year=.

Probing the Stochastic Machine: Engaging with LLMs in Statistics Curricula Through Veridical Data Science arXiv preprint arXiv:2508.00835 , year=

Reference 4

Resolution: verified exact; arxiv_id, observed 2026-07-01T15:15:47.622718Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation f437c453-1a36-4d64-ad0f-f985bbf07084 · outbound

This paper cites doi:10.17226/29292 , isbn =.

Probing the Stochastic Machine: Engaging with LLMs in Statistics Curricula Through Veridical Data Science doi:10.17226/29292 , isbn =

Reference 5

Resolution: malformed identifier; doi_truncated, observed 2026-06-30T04:24:19.203231Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 9ea5f2ee-b867-4813-b114-ef65d58e750e · outbound

This paper cites Proceedings of the 2024 conference on empirical methods in natural language processing , pages=.

Probing the Stochastic Machine: Engaging with LLMs in Statistics Curricula Through Veridical Data Science Proceedings of the 2024 conference on empirical methods in natural language processing , pages=

Reference 6

Resolution: unresolved; no resolver link, observed 2026-06-30T04:18:40.986797Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 69b1e304-ad5d-43b9-9d07-03c52e512f4a · outbound

This paper cites Advances in neural information processing systems , volume=.

Probing the Stochastic Machine: Engaging with LLMs in Statistics Curricula Through Veridical Data Science Advances in neural information processing systems , volume=

Reference 7

Resolution: unresolved; no resolver link, observed 2026-06-30T04:18:40.986797Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b6c7e8d3-cc51-4513-bb8f-5a94dc4d7a1c · outbound

This paper cites International Conference on Machine Learning , pages=.

Probing the Stochastic Machine: Engaging with LLMs in Statistics Curricula Through Veridical Data Science International Conference on Machine Learning , pages=

Reference 8

Resolution: unresolved; no resolver link, observed 2026-06-30T04:18:40.986797Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 789385cb-f9fc-41d8-a86c-b088532bc2dd · outbound

This paper cites Proceedings of the National Academy of Sciences , volume =.

Probing the Stochastic Machine: Engaging with LLMs in Statistics Curricula Through Veridical Data Science Proceedings of the National Academy of Sciences , volume =

Reference 9

Resolution: unresolved; no resolver link, observed 2026-06-30T04:18:40.986797Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 54482ad2-052b-4cd5-a3a2-7e9ea80c8b15 · outbound

This paper cites Lost in the middle: An emergent property from information retrieval demands in LLMs.

Probing the Stochastic Machine: Engaging with LLMs in Statistics Curricula Through Veridical Data Science Lost in the middle: An emergent property from information retrieval demands in LLMs

Reference 10

Resolution: verified exact; arxiv_id, observed 2026-07-01T15:15:47.619507Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 6f9fad2c-c60b-4483-9835-a5bf7ba35fc6 · outbound

This paper cites When Attention Sink Emerges in Language Models: An Empirical View.

Probing the Stochastic Machine: Engaging with LLMs in Statistics Curricula Through Veridical Data Science When Attention Sink Emerges in Language Models: An Empirical View

Reference 11

Resolution: verified exact; local_arxiv, observed 2026-07-01T15:15:47.616566Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation d8fbe8ba-c79f-410c-982a-5bcc0199a04a · outbound

This paper cites Harvard Data Science Review , volume=.

Probing the Stochastic Machine: Engaging with LLMs in Statistics Curricula Through Veridical Data Science Harvard Data Science Review , volume=

Reference 12

Resolution: unresolved; no resolver link, observed 2026-06-30T04:18:40.986797Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 54ff8286-e0c2-47fc-a32e-180a50c09ef5 · outbound

This paper cites Harvard Data Science Review , volume=.

Probing the Stochastic Machine: Engaging with LLMs in Statistics Curricula Through Veridical Data Science Harvard Data Science Review , volume=

Reference 13

Resolution: unresolved; no resolver link, observed 2026-06-30T04:18:40.986797Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2ae659a8-e46b-4fdf-a041-a1363f845cb9 · outbound

This paper cites Harvard Journal on Legislation , volume=.

Probing the Stochastic Machine: Engaging with LLMs in Statistics Curricula Through Veridical Data Science Harvard Journal on Legislation , volume=

Reference 14

Resolution: unresolved; no resolver link, observed 2026-06-30T04:18:40.986797Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7ed9979b-aac7-46f5-80fd-14e9ff265d1f · outbound

This paper cites New York University Law Review , pages=.

Probing the Stochastic Machine: Engaging with LLMs in Statistics Curricula Through Veridical Data Science New York University Law Review , pages=

Reference 15

Resolution: unresolved; no resolver link, observed 2026-06-30T04:18:40.986797Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.