Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-06T22:46:16.361001Z
Paper Citation Record · LEDGER
As of 21 August 2026, this Paper Citation Record lists 42 of 42 outbound references and 0 inbound Pith citation observations for arXiv:2506.20759.
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 2026-08-06T22:46:16.361001Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
42 of 42 outbound references displayed
External citation measurements
No source-named external measurement is stored.
Observation b274e79f-69c1-4080-8566-9a8cf564e249 · outbound
Agile Management for Machine Learning: A Systematic Mapping Study Kanban in software development: A systematic literature review,
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Agile Management for Machine Learning: A Systematic Mapping Study Applying scrum in data science projects,
Reference 4
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Agile Management for Machine Learning: A Systematic Mapping Study Being agile in a data science project,
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Agile Management for Machine Learning: A Systematic Mapping Study Recommended steps for thematic synthesis in software engineering,
Reference 10
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Agile Management for Machine Learning: A Systematic Mapping Study Ai lifecycle models need to be revised: An exploratory study in fintech,
Reference 12
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Agile Management for Machine Learning: A Systematic Mapping Study How to write ethical user stories? impacts of the eccola method,
Reference 13
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Observation 1b9d6a39-f42e-4856-8474-3f5bf6ee3f95 · outbound
Agile Management for Machine Learning: A Systematic Mapping Study The agile deployment of machine learning models in health- care,
Reference 14
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Agile Management for Machine Learning: A Systematic Mapping Study Utilizing user stories to bring ai ethics into practice in soft- ware engineering,
Reference 15
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Reference 16
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Agile Management for Machine Learning: A Systematic Mapping Study On the application of scrum in data science projects,
Reference 17
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Agile Management for Machine Learning: A Systematic Mapping Study What makes agile software development agile?
Reference 18
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Reference 19
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Agile Management for Machine Learning: A Systematic Mapping Study Agile clinical research: A data science approach to scrumban in clinical medicine,
Reference 20
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Reference 21
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Reference 22
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Reference 24
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Agile Management for Machine Learning: A Systematic Mapping Study Guidelines for conducting systematic mapping studies in software engineering: An update,
Reference 25
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Reference 27
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Reference 28
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Reference 29
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Agile Management for Machine Learning: A Systematic Mapping Study Identifying the most common frameworks data science teams use to structure and coordinate their projects,
Reference 30
Source-reported events for the cited work
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Reference 31
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Agile Management for Machine Learning: A Systematic Mapping Study Scrum development process,
Reference 34
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Agile Management for Machine Learning: A Systematic Mapping Study Toward a method engineering framework for project management and machine learning,
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Reference 41
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Observation 0bd395ec-cb68-4b29-beee-83ab9beb6612 · outbound
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Reference 42
Source-reported events for the cited work
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No inbound Pith citation observations are available.