Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-06-29T23:52:01.534465Z
Paper Citation Record · LEDGER
Analysis and Prediction of At-Risk Students Using Machine Learning Algorithms
As of 22 August 2026, this Paper Citation Record lists 9 of 9 outbound references and 0 inbound Pith citation observations for arXiv:2606.20617.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
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
A source-named dated measurement, never combined with another source.
Source: cited_works
Reference resolution
9 of 9 outbound references displayed
- verified exact1
- verified fuzzy0
- unresolved7
- parse uncertain0
- malformed identifier0
- metadata mismatch1
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation ec0191d4-0d17-46a5-9197-9c92ace837cf · outbound
This paper cites Internal corporate responsibility as a legitimacy strategy for branding and employee retention: A perspective of higher education institutions,.
Analysis and Prediction of At-Risk Students Using Machine Learning Algorithms Internal corporate responsibility as a legitimacy strategy for branding and employee retention: A perspective of higher education institutions,
Reference 1
- Resolution
- unresolved
- no resolver link, observed 2026-06-29T23:52:01.534465Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation f307cebd-baff-4c41-95e7-a6669ea1076b · outbound
This paper cites Improving student retention in institutions of higher education through machine learning: A sustainable approach,.
Analysis and Prediction of At-Risk Students Using Machine Learning Algorithms Improving student retention in institutions of higher education through machine learning: A sustainable approach,
Reference 2
- Resolution
- unresolved
- no resolver link, observed 2026-06-29T23:52:01.534465Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 495f17a2-be71-4a7e-827d-5b42d7b75d4a · outbound
This paper cites Total rewards and retention: Case study of higher education institutions in pakistan,.
Analysis and Prediction of At-Risk Students Using Machine Learning Algorithms Total rewards and retention: Case study of higher education institutions in pakistan,
Reference 3
- Resolution
- unresolved
- no resolver link, observed 2026-06-29T23:52:01.534465Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 9537eaec-9b54-4c61-acb9-8c442f488529 · outbound
This paper cites Machine learning model and ensemble algorithm for prediction of students’ retention and graduation in education,.
Analysis and Prediction of At-Risk Students Using Machine Learning Algorithms Machine learning model and ensemble algorithm for prediction of students’ retention and graduation in education,
Reference 4
- Resolution
- unresolved
- no resolver link, observed 2026-06-29T23:52:01.534465Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation c798942e-c466-437d-9b1e-9714ce361aa1 · outbound
This paper cites A systematic review on the deployment and effectiveness of data analytics in higher education to improve student outcomes,.
Analysis and Prediction of At-Risk Students Using Machine Learning Algorithms A systematic review on the deployment and effectiveness of data analytics in higher education to improve student outcomes,
Reference 5
- Resolution
- unresolved
- no resolver link, observed 2026-06-29T23:52:01.534465Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 33ec8f6c-23dd-4a84-8f03-a920004a2758 · outbound
This paper cites Employee Retention and Job Performance Attributes in Private Institutions of Higher Education,.
Analysis and Prediction of At-Risk Students Using Machine Learning Algorithms Employee Retention and Job Performance Attributes in Private Institutions of Higher Education,
Reference 6
- Resolution
- unresolved
- no resolver link, observed 2026-06-29T23:52:01.534465Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 8e25aa2b-6fae-42e3-8f0b-95802a484d58 · outbound
This paper cites ArXiv abs/2405.00574 (2024) https://doi.org/ 10.1109/uemcon62879.2024.10754673.
Analysis and Prediction of At-Risk Students Using Machine Learning Algorithms ArXiv abs/2405.00574 (2024) https://doi.org/ 10.1109/uemcon62879.2024.10754673
Reference 7
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-06-29T23:54:02.252780Z
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 fb7e4a8f-8f3b-4717-b14f-b81f80c5a702 · outbound
This paper cites Forecasting Student Attrition Using Machine Learning.
Analysis and Prediction of At-Risk Students Using Machine Learning Algorithms Forecasting Student Attrition Using Machine Learning
Reference 8
- Resolution
- unresolved
- no resolver link, observed 2026-06-29T23:52:01.534465Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 409bc211-634f-4607-9a21-b1ddb59860b1 · outbound
This paper cites Student Retention Model via Machine Learning and Predictive analysis,.
Analysis and Prediction of At-Risk Students Using Machine Learning Algorithms Student Retention Model via Machine Learning and Predictive analysis,
Reference 9
- Resolution
- verified exact
- arxiv_id, observed 2026-06-29T23:54:02.255762Z
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.
Pith citing papers
No inbound Pith citation observations are available.