Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-09T17:21:02.708760Z
Paper Citation Record · LEDGER
As of 22 August 2026, this Paper Citation Record lists 45 of 45 outbound references and 1 inbound Pith citation observation for arXiv:2502.00902.
A citation records a reference. It does not transfer a finding from one paper to another.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-09T17:21:02.708760Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-05-09T19:17:06.371004Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-11T15:46:48.531430Z
45 of 45 outbound references displayed
External citation measurements
No source-named external measurement is stored.
Observation 5c6c8dae-481f-4902-998d-fe375ee63bb9 · outbound
More Rigorous Software Engineering Would Improve Reproducibility in Machine Learning Research Unresolved cited work
Reference 1
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation a9cd3936-8acb-4dfc-943e-ddc8534375b0 · outbound
More Rigorous Software Engineering Would Improve Reproducibility in Machine Learning Research JAX : composable transformations of P ython+ N um P y programs, 2025
Reference 2
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 4a8c74c0-2c13-49fc-a715-4c79916b4228 · outbound
More Rigorous Software Engineering Would Improve Reproducibility in Machine Learning Research The ml test score: A rubric for ml production readiness and technical debt reduction
Reference 3
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 fff995f2-931b-439d-81aa-db972f0f1aa8 · outbound
More Rigorous Software Engineering Would Improve Reproducibility in Machine Learning Research Unresolved cited work
Reference 4
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 fb659e7b-3380-4d94-a21b-740e1f10fec2 · outbound
More Rigorous Software Engineering Would Improve Reproducibility in Machine Learning Research Pep 751 – a file format to record python dependencies for installation reproducibility, 2024
Reference 5
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 17590b62-7985-491b-8708-1541cadca0ca · outbound
More Rigorous Software Engineering Would Improve Reproducibility in Machine Learning Research Pep 621 – storing project metadata in pyproject.toml, 2020
Reference 6
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 eae375fe-e417-4ef2-bfb3-8585dafcece6 · outbound
More Rigorous Software Engineering Would Improve Reproducibility in Machine Learning Research Conda documentation, 2025
Reference 7
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 5a9738f7-77db-4591-92e8-0325af11a491 · outbound
More Rigorous Software Engineering Would Improve Reproducibility in Machine Learning Research Chex documentation, 2025
Reference 8
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 58557f46-9683-44ae-9752-3d9ef8cdac0a · outbound
More Rigorous Software Engineering Would Improve Reproducibility in Machine Learning Research Manual for package pgfplots
Reference 9
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 e67c05c6-ba75-47d0-82f2-7aebb58672fd · outbound
More Rigorous Software Engineering Would Improve Reproducibility in Machine Learning Research Pdfx, 2021
Reference 10
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 0f02ab99-c6ce-4eb1-9c23-6b3c842f3e20 · outbound
More Rigorous Software Engineering Would Improve Reproducibility in Machine Learning Research 38 Mason Christopher E
Reference 11
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 91836bbc-c139-452a-9533-a0ae5b6ebaac · outbound
More Rigorous Software Engineering Would Improve Reproducibility in Machine Learning Research Hatch documentation, 2025
Reference 12
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 79f16c38-6331-4360-a8e9-88571f759e10 · outbound
More Rigorous Software Engineering Would Improve Reproducibility in Machine Learning Research Reproducibility standards for machine learning in the life sciences
Reference 13
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 85da7742-2414-49eb-87ec-42fb7bae72db · outbound
More Rigorous Software Engineering Would Improve Reproducibility in Machine Learning Research Improving reproducibility and reusability in the journal of cheminformatics
Reference 14
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 f897ca57-b854-4d4d-af10-c1ecfb4f9a5b · outbound
More Rigorous Software Engineering Would Improve Reproducibility in Machine Learning Research Artificial intelligence faces reproducibility crisis
Reference 15
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 a6ca3492-a830-4e37-b334-32796fc7b51c · outbound
More Rigorous Software Engineering Would Improve Reproducibility in Machine Learning Research Software engineering for computational science: Past, present, future
Reference 16
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 d00e3c23-1ba2-4bf6-ad66-ce63eeac832d · outbound
More Rigorous Software Engineering Would Improve Reproducibility in Machine Learning Research Ten simple rules for developing usable software in computational biology
Reference 17
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 a24008c2-0cb8-4a1c-bf45-0d33b3d2ec0b · outbound
More Rigorous Software Engineering Would Improve Reproducibility in Machine Learning Research mypy, 2025
Reference 18
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 d53d3246-4699-45e8-82a8-87b1db8b8888 · outbound
More Rigorous Software Engineering Would Improve Reproducibility in Machine Learning Research Automatic differentiation in pytorch
Reference 19
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 a31e011b-fb42-4e19-a2e1-2fa55784de25 · outbound
More Rigorous Software Engineering Would Improve Reproducibility in Machine Learning Research Eglen, Daniel S
Reference 20
Source-reported events for the cited work
correction dated 2019-06-14. Source: crossref record 10.1371/journal.pcbi.1007142->10.1371/journal.pcbi.1004947:correction, observed 2026-07-11T03:09:24.399304+00:00. This notice travels one citation hop only.
Observation f172ccf6-5214-4344-a3e2-62bb4a131c4c · outbound
More Rigorous Software Engineering Would Improve Reproducibility in Machine Learning Research Improving reproducibility in machine learning research (a report from the neurips 2019 reproducibility program)
Reference 21
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 1dbe4a12-7813-40a3-85ed-4220a55523d8 · outbound
More Rigorous Software Engineering Would Improve Reproducibility in Machine Learning Research Requirements file format - pip documentation v25.0, 2025
Reference 22
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 25ec3d12-62ee-4c8d-ad39-87e8b55cc816 · outbound
More Rigorous Software Engineering Would Improve Reproducibility in Machine Learning Research The logic of scientific discovery
Reference 23
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation b04125c1-edcc-4a62-8638-3e86a5890f57 · outbound
More Rigorous Software Engineering Would Improve Reproducibility in Machine Learning Research Ml reproducibility challenge, 2025
Reference 24
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 0c81087e-e80a-436a-8dbd-f94a9a70d5e9 · outbound
More Rigorous Software Engineering Would Improve Reproducibility in Machine Learning Research Unresolved cited work
Reference 25
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 2e84c9fd-5805-493e-aa61-7c79948b8e93 · outbound
More Rigorous Software Engineering Would Improve Reproducibility in Machine Learning Research Pytest documentation, 2025
Reference 26
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 0fc026d6-a8fc-42f9-b097-59db64216a48 · outbound
More Rigorous Software Engineering Would Improve Reproducibility in Machine Learning Research unittest - unit testing framework, 2025
Reference 27
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 f943ea31-8ef3-456e-84cf-4d902998c520 · outbound
More Rigorous Software Engineering Would Improve Reproducibility in Machine Learning Research Packaging python-projects, 2025
Reference 28
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 cf967877-776d-4c5f-9d13-bb9080759b2a · outbound
More Rigorous Software Engineering Would Improve Reproducibility in Machine Learning Research Reproducibility, 2024
Reference 29
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 e7c4d872-757a-477b-993d-068e82191d42 · outbound
More Rigorous Software Engineering Would Improve Reproducibility in Machine Learning Research A step toward quantifying independently reproducible machine learning research
Reference 30
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 1fd002b3-c476-45bf-a2c4-352cbbaa75e0 · outbound
More Rigorous Software Engineering Would Improve Reproducibility in Machine Learning Research Research reproducibility as a survival analysis
Reference 31
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 24c024e5-aef4-4efc-a281-c53d6ff870ec · outbound
More Rigorous Software Engineering Would Improve Reproducibility in Machine Learning Research Does the market of citations reward reproducible work? In Proceedings of the 2023 ACM Conference on Reproducibility and Replicability, pp.\ 89--96, 2023
Reference 32
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 45e830d7-33fe-42ac-af66-0cd70c1b5580 · outbound
More Rigorous Software Engineering Would Improve Reproducibility in Machine Learning Research A siren song of open source reproducibility, examples from machine learning
Reference 33
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 90823b0f-639f-4c18-897d-4ae54ce014ab · outbound
More Rigorous Software Engineering Would Improve Reproducibility in Machine Learning Research Beautiful soup documentation, 2023
Reference 34
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 4b47bd54-fca8-4bb6-85ac-482c231910e8 · outbound
More Rigorous Software Engineering Would Improve Reproducibility in Machine Learning Research Pep 484 – type hints, 2014
Reference 35
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 b386d9f9-28b1-4370-88cd-5f46efaec6fe · outbound
More Rigorous Software Engineering Would Improve Reproducibility in Machine Learning Research Ten simple rules for reproducible computational research
Reference 36
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 2921b8e5-d24f-4a9d-b89f-308c10c2440c · outbound
More Rigorous Software Engineering Would Improve Reproducibility in Machine Learning Research Setuptools documentation, 2025
Reference 37
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 ae4d109a-8421-4bbb-a0ee-b073b3d267b1 · outbound
More Rigorous Software Engineering Would Improve Reproducibility in Machine Learning Research Smith, Thomas Kluyver, and Alyssa Coghlan
Reference 38
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 6e2775f5-9af4-4c83-8b72-c8af5cdfe946 · outbound
More Rigorous Software Engineering Would Improve Reproducibility in Machine Learning Research The need for open source software in machine learning
Reference 39
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 238f45b6-2270-40dc-a59f-293f61525e03 · outbound
More Rigorous Software Engineering Would Improve Reproducibility in Machine Learning Research Sphinx documentation, 2025
Reference 40
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 58272dbb-24d9-4d2a-8322-5b82228d62d8 · outbound
More Rigorous Software Engineering Would Improve Reproducibility in Machine Learning Research Tips for releasing research code in machine learning (with official neurips 2020 recommendations), 2020
Reference 41
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 5a2a7d94-946e-4a6b-8ac0-1e85e8816f4b · outbound
More Rigorous Software Engineering Would Improve Reproducibility in Machine Learning Research A practical taxonomy of reproducibility for machine learning research
Reference 42
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 07993a90-ce3a-4a0f-9c3c-abf5ca927bd3 · outbound
More Rigorous Software Engineering Would Improve Reproducibility in Machine Learning Research Pep 8 -- style guide for python code, 2001
Reference 43
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 4e8516b2-1fbf-4ba2-ae7a-3294e9a64063 · outbound
More Rigorous Software Engineering Would Improve Reproducibility in Machine Learning Research The five pillars of computational reproducibility: bioinformatics and beyond
Reference 44
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 c2dae1c6-41be-4554-a80c-346993183700 · outbound
More Rigorous Software Engineering Would Improve Reproducibility in Machine Learning Research write newline
Reference 45
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation a2160e89-6fb9-4155-810b-0a97bafab851 · inbound
Can Coding Agents Reproduce Findings in Computational Materials Science? More Rigorous Software Engineering Would Improve Reproducibility in Machine Learning Research
Reference 14
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.