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Paper Citation Record · LEDGER

A Privacy-Preserving Framework Using Remote Data Science for Inter-Institutional Student Retention Prediction

As of 13 August 2026, this Paper Citation Record lists 22 of 22 outbound references and 0 inbound Pith citation observations for arXiv:2606.12845.

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

pith.paper-citation-record.v1
2606.12845 v1

Coverage vector

measured 22 of 22 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-06-27T06:49:40.139509Z

measured 22 of 22 standing notices

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Source: scholarly_work_events, retraction_status_cache, observed 2026-08-13T06:32:02.005865+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

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measured 0 of 1 external citation measurements

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Source: cited_works

Reference resolution

22 of 22 outbound references displayed

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External citation measurements

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Outbound references

Observation 40d7c196-5292-40cc-8c41-2cd30a79efe9 · outbound

This paper cites Why have college completion rates increased?.

A Privacy-Preserving Framework Using Remote Data Science for Inter-Institutional Student Retention Prediction Why have college completion rates increased?

Reference 1

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Observation f39d90e4-58c7-4995-b9a1-ce48760093e4 · outbound

This paper cites Predicting student dropout: A machine learning approach,.

A Privacy-Preserving Framework Using Remote Data Science for Inter-Institutional Student Retention Prediction Predicting student dropout: A machine learning approach,

Reference 2

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Observation 62a3c632-f5a8-4ac4-9248-b75aceebee24 · outbound

This paper cites Integrating categorical and continuous data in a cluster-then-classify methodology for predicting undergraduate student success,.

A Privacy-Preserving Framework Using Remote Data Science for Inter-Institutional Student Retention Prediction Integrating categorical and continuous data in a cluster-then-classify methodology for predicting undergraduate student success,

Reference 3

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Observation 241fec14-ec33-4f28-98bc-18847ad0339e · outbound

This paper cites Predicting university dropout through data mining: A systematic literature,.

A Privacy-Preserving Framework Using Remote Data Science for Inter-Institutional Student Retention Prediction Predicting university dropout through data mining: A systematic literature,

Reference 4

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Observation 30ba0fec-1d1c-48c0-9c9d-aec114293459 · outbound

This paper cites Student clustering procedure according to dropout risk to improve student management in higher education,.

A Privacy-Preserving Framework Using Remote Data Science for Inter-Institutional Student Retention Prediction Student clustering procedure according to dropout risk to improve student management in higher education,

Reference 5

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Observation c829ee6f-4053-4cc3-880a-6fd34be9d761 · outbound

This paper cites Modeling and experi- mental design for MOOC dropout prediction: A replication perspective,.

A Privacy-Preserving Framework Using Remote Data Science for Inter-Institutional Student Retention Prediction Modeling and experi- mental design for MOOC dropout prediction: A replication perspective,

Reference 6

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Observation 4d582b53-1cac-4ee3-bebf-29c449ba24b1 · outbound

This paper cites Predicting students drop out: A case study,.

A Privacy-Preserving Framework Using Remote Data Science for Inter-Institutional Student Retention Prediction Predicting students drop out: A case study,

Reference 7

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Observation 48b80d25-35ef-4226-827c-afecbc8d853f · outbound

This paper cites Early dropout prediction using data mining: A case study with high school students,.

A Privacy-Preserving Framework Using Remote Data Science for Inter-Institutional Student Retention Prediction Early dropout prediction using data mining: A case study with high school students,

Reference 8

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Observation ee2144e9-43ff-40c4-9807-8ce9ba46cfb7 · outbound

This paper cites Predictive learning analytics using deep learning model in MOOCs courses videos,.

A Privacy-Preserving Framework Using Remote Data Science for Inter-Institutional Student Retention Prediction Predictive learning analytics using deep learning model in MOOCs courses videos,

Reference 9

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Observation fed7f1db-8c1b-4a0b-940b-14c398e84252 · outbound

This paper cites Extracting topological features to identify at-risk students using ML and GCN models,.

A Privacy-Preserving Framework Using Remote Data Science for Inter-Institutional Student Retention Prediction Extracting topological features to identify at-risk students using ML and GCN models,

Reference 10

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Observation 53d922bb-416b-4d94-b34c-b561853f97fd · outbound

This paper cites Learning analytics should not promote one size fits all,.

A Privacy-Preserving Framework Using Remote Data Science for Inter-Institutional Student Retention Prediction Learning analytics should not promote one size fits all,

Reference 11

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Observation 29e4d118-e105-4ae2-b048-99dcde9e2848 · outbound

This paper cites Cross- institutional transfer learning for educational models: Implications for model performance, fairness, and equity,.

A Privacy-Preserving Framework Using Remote Data Science for Inter-Institutional Student Retention Prediction Cross- institutional transfer learning for educational models: Implications for model performance, fairness, and equity,

Reference 12

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Observation 332aaa6c-b9b6-4acb-84ce-84c6852ef1f7 · outbound

This paper cites Introducing TensorFlow Federated,.

A Privacy-Preserving Framework Using Remote Data Science for Inter-Institutional Student Retention Prediction Introducing TensorFlow Federated,

Reference 13

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Observation 71e7524e-ebc4-4415-a30b-d6075cb3ddbb · outbound

This paper cites Model inversion attacks that exploit confidence information and basic countermeasures,.

A Privacy-Preserving Framework Using Remote Data Science for Inter-Institutional Student Retention Prediction Model inversion attacks that exploit confidence information and basic countermeasures,

Reference 14

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Observation 2f66e169-d0a2-4567-bff3-85fbd2a48570 · outbound

This paper cites Membership inference attacks against machine learning models,.

A Privacy-Preserving Framework Using Remote Data Science for Inter-Institutional Student Retention Prediction Membership inference attacks against machine learning models,

Reference 15

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Observation 8e1f688b-29da-47ad-9392-49ae488b8c67 · outbound

This paper cites DataSHIELD: Mitigating disclosure risk in a multi- site federated analysis platform,.

A Privacy-Preserving Framework Using Remote Data Science for Inter-Institutional Student Retention Prediction DataSHIELD: Mitigating disclosure risk in a multi- site federated analysis platform,

Reference 16

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Observation a0033a0b-7e3e-4370-8791-6d82ad131f41 · outbound

This paper cites Beyond Privacy Trade-offs with Structured Transparency.

A Privacy-Preserving Framework Using Remote Data Science for Inter-Institutional Student Retention Prediction Beyond Privacy Trade-offs with Structured Transparency

Reference 17

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arxiv_id, observed 2026-07-03T14:58:32.920926Z

Source-reported events for the cited work

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Observation 5055105c-8347-4297-9223-bbaa346b68c0 · outbound

This paper cites SDV: An open source library for synthetic data genera- tion,.

A Privacy-Preserving Framework Using Remote Data Science for Inter-Institutional Student Retention Prediction SDV: An open source library for synthetic data genera- tion,

Reference 18

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Observation a34f3837-216d-45d6-b926-baa2f8588821 · outbound

This paper cites Faketucky: OpenSDP college-going dataset,.

A Privacy-Preserving Framework Using Remote Data Science for Inter-Institutional Student Retention Prediction Faketucky: OpenSDP college-going dataset,

Reference 19

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Observation e0d1aff5-7fcf-416b-ade5-54d1d80fe1c1 · outbound

This paper cites SyftBox,.

A Privacy-Preserving Framework Using Remote Data Science for Inter-Institutional Student Retention Prediction SyftBox,

Reference 20

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Observation f2b48240-2989-40a9-899d-3864cd09abaa · outbound

This paper cites Federated learning analytics: Investigating the privacy-performance trade-off,.

A Privacy-Preserving Framework Using Remote Data Science for Inter-Institutional Student Retention Prediction Federated learning analytics: Investigating the privacy-performance trade-off,

Reference 21

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Observation 4c004c16-bf1c-4cbc-8666-195003f8e532 · outbound

This paper cites Differential privacy,.

A Privacy-Preserving Framework Using Remote Data Science for Inter-Institutional Student Retention Prediction Differential privacy,

Reference 22

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Pith citing papers

No inbound Pith citation observations are available.