Paper Citation Record · LEDGER

A Structured Reasoning Framework for Unbalanced Data Classification Using Probabilistic Models

As of 9 August 2026, this Paper Citation Record lists 21 of 21 outbound references and 0 inbound Pith citation observations for arXiv:2502.03386.

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

pith.paper-citation-record.v1
2502.03386 v1

Coverage vector

measured 21 of 21 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-09T04:56:43.680754Z

measured 21 of 21 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+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

21 of 21 outbound references displayed

verified exact4
verified fuzzy11
unresolved6
parse uncertain0
malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 18bfc459-abe2-419e-b3ba-b1dee3de802c · outbound

This paper cites Survival prediction across diverse cancer types using neural networks.

A Structured Reasoning Framework for Unbalanced Data Classification Using Probabilistic Models Survival prediction across diverse cancer types using neural networks

Reference 1

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Source-reported events for the cited work

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Observation 13cb969e-59c9-4cc8-a00a-037b93002580 · outbound

This paper cites Time-Series Nested Reinforcement Learning for Dynamic Risk Control in Nonlinear Financial Markets,.

A Structured Reasoning Framework for Unbalanced Data Classification Using Probabilistic Models Time-Series Nested Reinforcement Learning for Dynamic Risk Control in Nonlinear Financial Markets,

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-09T04:56:43.554054Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8d77c1c8-d9ea-43fe-bece-bfa1bb2928a8 · outbound

This paper cites Credit Default Prediction with Machine Learning: A Comparative Study and Interpretability Insights.

A Structured Reasoning Framework for Unbalanced Data Classification Using Probabilistic Models Credit Default Prediction with Machine Learning: A Comparative Study and Interpretability Insights

Reference 3

Resolution: verified exact; arxiv_id_nonexistent, observed 2026-08-09T04:56:44.182509Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation d4952a64-175a-4925-93c5-77463167d074 · outbound

This paper cites Artificial Intelligence- Driven Risk Assessment and Control in Financial Derivatives: Exploring Deep Learning and Ensemble Models,.

A Structured Reasoning Framework for Unbalanced Data Classification Using Probabilistic Models Artificial Intelligence- Driven Risk Assessment and Control in Financial Derivatives: Exploring Deep Learning and Ensemble Models,

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-09T04:56:43.567184Z

Source-reported events for the cited work

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Observation 8d905fcd-484c-4178-9300-2d2edd1bbcba · outbound

This paper cites Deep Learning-Based Gesture Key Point Detection for Human-Computer Interaction Applications,.

A Structured Reasoning Framework for Unbalanced Data Classification Using Probabilistic Models Deep Learning-Based Gesture Key Point Detection for Human-Computer Interaction Applications,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T04:56:44.433181Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation f09384dc-8553-499d-b225-a7307747f717 · outbound

This paper cites Feature selection in the data stream based on incremental Markov boundary learning,.

A Structured Reasoning Framework for Unbalanced Data Classification Using Probabilistic Models Feature selection in the data stream based on incremental Markov boundary learning,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T04:56:44.413511Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 9dbf8f42-1554-431a-b5aa-1443fcd87f1d · outbound

This paper cites MC-RGN: Residual Graph Neural Networks based on Markov Chain for sequential recommendation,.

A Structured Reasoning Framework for Unbalanced Data Classification Using Probabilistic Models MC-RGN: Residual Graph Neural Networks based on Markov Chain for sequential recommendation,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T04:56:44.389061Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation a8664e55-2325-4176-a497-f6e37eea72c8 · outbound

This paper cites A modern approach to transition analysis and process mining with Markov models in education,.

A Structured Reasoning Framework for Unbalanced Data Classification Using Probabilistic Models A modern approach to transition analysis and process mining with Markov models in education,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T04:56:44.369422Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 9eefebc2-3428-4ea2-a8ce-6887923d1231 · outbound

This paper cites Data mining techniques for web mining: a survey,.

A Structured Reasoning Framework for Unbalanced Data Classification Using Probabilistic Models Data mining techniques for web mining: a survey,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T04:56:44.346565Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 7ce797e5-c2c2-4a81-adf9-bc9355fb611d · outbound

This paper cites Leveraging Generative Adversarial Networks for Addressing Data Imbalance in Financial Market Supervision.

A Structured Reasoning Framework for Unbalanced Data Classification Using Probabilistic Models Leveraging Generative Adversarial Networks for Addressing Data Imbalance in Financial Market Supervision

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-09T04:56:43.608999Z

Source-reported events for the cited work

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Observation 51564057-9756-4465-8ec9-40792fdf2c39 · outbound

This paper cites Collaborative Optimization in Financial Data Mining Through Deep Learning and ResNeXt.

A Structured Reasoning Framework for Unbalanced Data Classification Using Probabilistic Models Collaborative Optimization in Financial Data Mining Through Deep Learning and ResNeXt

Reference 11

Resolution: verified exact; local_arxiv, observed 2026-08-09T04:56:43.990544Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 432bcc6a-4860-421c-9c7b-9ccadc94916c · outbound

This paper cites Robust Graph Neural Networks for Stability Analysis in Dynamic Networks,.

A Structured Reasoning Framework for Unbalanced Data Classification Using Probabilistic Models Robust Graph Neural Networks for Stability Analysis in Dynamic Networks,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T04:56:44.325724Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation e12c66c0-f0fd-4d4b-9a98-1224852fd3db · outbound

This paper cites The Synergistic Role of Deep Learning and Neural Architecture Search in Advancing Artificial Intelligence,.

A Structured Reasoning Framework for Unbalanced Data Classification Using Probabilistic Models The Synergistic Role of Deep Learning and Neural Architecture Search in Advancing Artificial Intelligence,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T04:56:44.304861Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation b7b5271f-3fec-455c-846e-ef68743080a3 · outbound

This paper cites Reinforcement Learning-Based Q-Learning Approach for Optimizing Data Mining in Dynamic Environments.

A Structured Reasoning Framework for Unbalanced Data Classification Using Probabilistic Models Reinforcement Learning-Based Q-Learning Approach for Optimizing Data Mining in Dynamic Environments

Reference 14

Resolution: verified exact; arxiv_id_nonexistent, observed 2026-08-09T04:56:43.962638Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 33c63580-2b28-4084-ac82-c04788010a42 · outbound

This paper cites Advanced Risk Prediction and Stability Assessment of Banks Using Time Series Transformer Models.

A Structured Reasoning Framework for Unbalanced Data Classification Using Probabilistic Models Advanced Risk Prediction and Stability Assessment of Banks Using Time Series Transformer Models

Reference 15

Resolution: verified exact; local_arxiv, observed 2026-08-09T04:56:43.757441Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation d7e35faf-64aa-426e-85ea-35ea8681146f · outbound

This paper cites Mining Multimodal Data with Sparse Decomposition and Adaptive Weighting,.

A Structured Reasoning Framework for Unbalanced Data Classification Using Probabilistic Models Mining Multimodal Data with Sparse Decomposition and Adaptive Weighting,

Reference 16

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Source-reported events for the cited work

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Observation 757bee1a-8fd4-400e-91cb-89158e2b87f8 · outbound

This paper cites Machine Learning Techniques for Pattern Recognition in High-Dimensional Data Mining.

A Structured Reasoning Framework for Unbalanced Data Classification Using Probabilistic Models Machine Learning Techniques for Pattern Recognition in High-Dimensional Data Mining

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-09T04:56:43.654049Z

Source-reported events for the cited work

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Observation f650016b-778f-4b69-a4a0-0fbe6b017ac3 · outbound

This paper cites Heart disease prediction using logistic regression and random forest classifier,.

A Structured Reasoning Framework for Unbalanced Data Classification Using Probabilistic Models Heart disease prediction using logistic regression and random forest classifier,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T04:56:44.262534Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 604aba4d-f7f9-4fa8-ad48-a617f565c15c · outbound

This paper cites Hybrid data mining technique based breast cancer prediction,.

A Structured Reasoning Framework for Unbalanced Data Classification Using Probabilistic Models Hybrid data mining technique based breast cancer prediction,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T04:56:44.241450Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 6830f469-6d0f-4062-8677-c3e95c8fe665 · outbound

This paper cites What is the best predictor of word difficulty? A case of data mining using random forest,.

A Structured Reasoning Framework for Unbalanced Data Classification Using Probabilistic Models What is the best predictor of word difficulty? A case of data mining using random forest,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T04:56:44.221886Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation e1423472-a52a-46f8-b977-4e8c60fc78f7 · outbound

This paper cites Enterprise marketing strategy using big data mining technology combined with XGBoost model in the new economic era,.

A Structured Reasoning Framework for Unbalanced Data Classification Using Probabilistic Models Enterprise marketing strategy using big data mining technology combined with XGBoost model in the new economic era,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T04:56:44.201788Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Pith citing papers

No inbound Pith citation observations are available.