Paper Citation Record · LEDGER

FeatureCuts: Feature Selection for Large Data by Optimizing the Cutoff

As of 21 August 2026, this Paper Citation Record lists 44 of 44 outbound references and 1 inbound Pith citation observation for arXiv:2508.00954.

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

pith.paper-citation-record.v1
2508.00954 v1

Coverage vector

measured 44 of 44 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T10:19:14.889675Z

measured 45 of 45 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T10:03:22.975907Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: pith, observed 2026-08-06T10:03:23.069763Z

Reference resolution

44 of 44 outbound references displayed

verified exact9
verified fuzzy25
unresolved10
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 4a8e7a92-88b1-4411-875a-492cc279d30e · outbound

This paper cites an unresolved cited work.

FeatureCuts: Feature Selection for Large Data by Optimizing the Cutoff Unresolved cited work

Reference 1

Resolution: unresolved; raw_fallback, observed 2026-08-06T10:19:25.765254Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 5b671814-94e2-4183-9117-5ebd4f6a1579 · outbound

This paper cites Feature selection: A data perspective,.

FeatureCuts: Feature Selection for Large Data by Optimizing the Cutoff Feature selection: A data perspective,

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-06T10:19:08.593045Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5dc034d3-b0e0-47c4-9dca-8b114fa6408d · outbound

This paper cites Language Models are Few-Shot Learners.

FeatureCuts: Feature Selection for Large Data by Optimizing the Cutoff Language Models are Few-Shot Learners

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-06T10:19:08.687155Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 693de6c7-35bd-495c-a92b-a081cb8af7b6 · outbound

This paper cites On the Opportunities and Risks of Foundation Models.

FeatureCuts: Feature Selection for Large Data by Optimizing the Cutoff On the Opportunities and Risks of Foundation Models

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-06T10:19:08.876363Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9aaa9dc0-31fe-4463-b000-dde0dd713457 · outbound

This paper cites Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translation.

FeatureCuts: Feature Selection for Large Data by Optimizing the Cutoff Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translation

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-06T10:19:09.025114Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cfe40c77-f5ff-4299-a383-6fb6793b7288 · outbound

This paper cites Feature Selection: A Data Perspective.

FeatureCuts: Feature Selection for Large Data by Optimizing the Cutoff Feature Selection: A Data Perspective

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-06T10:19:09.193206Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a8b1728f-dcde-4a01-9553-751427ac868d · outbound

This paper cites A review of feature selection and its methods,.

FeatureCuts: Feature Selection for Large Data by Optimizing the Cutoff A review of feature selection and its methods,

Reference 7

Resolution: verified exact; doi, observed 2026-08-06T10:19:17.285674Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation ab866385-9d83-48f4-9ef8-afd0a9d2183d · outbound

This paper cites A review on feature selection methods for classification tasks,.

FeatureCuts: Feature Selection for Large Data by Optimizing the Cutoff A review on feature selection methods for classification tasks,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T10:19:25.420411Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation f73011f9-5e5f-4bde-80bd-d2cddcdf5a80 · outbound

This paper cites Feature selection methods: Case of filter and wrapper approaches for maximising classifi- cation accuracy,.

FeatureCuts: Feature Selection for Large Data by Optimizing the Cutoff Feature selection methods: Case of filter and wrapper approaches for maximising classifi- cation accuracy,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T10:19:25.083591Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 09932971-c637-45c2-b626-e624bc04e5d1 · outbound

This paper cites A hybrid genetic algorithm with wrapper-embedded approaches for feature selection,.

FeatureCuts: Feature Selection for Large Data by Optimizing the Cutoff A hybrid genetic algorithm with wrapper-embedded approaches for feature selection,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T10:19:24.740812Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 17954939-dd18-4226-b7da-32c309ba3e84 · outbound

This paper cites Evolutionary computation for feature selection in classification: A comprehensive survey of solutions, applications and challenges,.

FeatureCuts: Feature Selection for Large Data by Optimizing the Cutoff Evolutionary computation for feature selection in classification: A comprehensive survey of solutions, applications and challenges,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T10:19:24.414101Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation c172c548-4b85-4ef1-965f-21999d5e48cf · outbound

This paper cites Feature selection algorithm based on optimized genetic algorithm and the application in high-dimensional data processing,.

FeatureCuts: Feature Selection for Large Data by Optimizing the Cutoff Feature selection algorithm based on optimized genetic algorithm and the application in high-dimensional data processing,

Reference 12

Resolution: verified exact; doi, observed 2026-08-06T10:19:17.013208Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation fc334736-9132-4c60-bbe4-61eb2c8b6193 · outbound

This paper cites Feature selec- tion in high dimensional data by a filter-based genetic algorithm,.

FeatureCuts: Feature Selection for Large Data by Optimizing the Cutoff Feature selec- tion in high dimensional data by a filter-based genetic algorithm,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T10:19:24.132193Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 47046317-4b26-4e49-8870-8d967c568af5 · outbound

This paper cites Hybrid filter and genetic algorithm-based feature selection for improving cancer classification in high-dimensional microarray data,.

FeatureCuts: Feature Selection for Large Data by Optimizing the Cutoff Hybrid filter and genetic algorithm-based feature selection for improving cancer classification in high-dimensional microarray data,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T10:19:23.811731Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 115b91f5-9116-40d8-9dde-359e9b198da4 · outbound

This paper cites Practical challenges and recommendations of filter methods for feature selection,.

FeatureCuts: Feature Selection for Large Data by Optimizing the Cutoff Practical challenges and recommendations of filter methods for feature selection,

Reference 15

Resolution: verified exact; doi, observed 2026-08-06T10:19:16.730757Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 52abe968-87f5-4e07-8ee4-00b30b290739 · outbound

This paper cites uefs: An efficient and comprehensive ensemble-based feature selection methodology to select informative features,.

FeatureCuts: Feature Selection for Large Data by Optimizing the Cutoff uefs: An efficient and comprehensive ensemble-based feature selection methodology to select informative features,

Reference 16

Resolution: verified exact; doi, observed 2026-08-06T10:19:16.426381Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 3ccd0c06-c95d-4254-aec4-c7275e9b103f · outbound

This paper cites A hybrid feature selection method for classification purposes,.

FeatureCuts: Feature Selection for Large Data by Optimizing the Cutoff A hybrid feature selection method for classification purposes,

Reference 17

Resolution: verified exact; doi, observed 2026-08-06T10:19:16.114264Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 111e6551-1a5f-4234-be75-cf62c49cb0e3 · outbound

This paper cites Hybrid binary bat enhanced particle swarm optimization algorithm for solving feature selection problems,.

FeatureCuts: Feature Selection for Large Data by Optimizing the Cutoff Hybrid binary bat enhanced particle swarm optimization algorithm for solving feature selection problems,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T10:19:23.440739Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 4f6832e8-34bf-44ef-b40a-536427307a11 · outbound

This paper cites A feature selection algorithm performance metric for comparative analysis,.

FeatureCuts: Feature Selection for Large Data by Optimizing the Cutoff A feature selection algorithm performance metric for comparative analysis,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T10:19:23.071572Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation eb3f9a8f-8e2a-430c-ae77-49de393ebd8e · outbound

This paper cites Hierarchical harris hawks optimizer for feature selection,.

FeatureCuts: Feature Selection for Large Data by Optimizing the Cutoff Hierarchical harris hawks optimizer for feature selection,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T10:19:22.800263Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation a897b40a-fe47-4ba7-80d8-f3c7f4619cab · outbound

This paper cites Bayesian Optimization: Open source constrained global optimization tool for Python,.

FeatureCuts: Feature Selection for Large Data by Optimizing the Cutoff Bayesian Optimization: Open source constrained global optimization tool for Python,

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-06T10:19:11.490182Z

Source-reported events for the cited work

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Observation 8fc14caa-6028-43ec-ab46-c3ac751303fb · outbound

This paper cites Golden-section search,.

FeatureCuts: Feature Selection for Large Data by Optimizing the Cutoff Golden-section search,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T10:19:22.487627Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 70546303-0f62-484c-b668-f8e02a3ad6bb · outbound

This paper cites Py fs: A python package for feature selection using meta-heuristic optimization algorithms,.

FeatureCuts: Feature Selection for Large Data by Optimizing the Cutoff Py fs: A python package for feature selection using meta-heuristic optimization algorithms,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T10:19:22.268733Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation e528471b-7897-4b83-b34d-d75989dab1f5 · outbound

This paper cites Binary genetic swarm optimization: A combination of ga and pso for feature selection,.

FeatureCuts: Feature Selection for Large Data by Optimizing the Cutoff Binary genetic swarm optimization: A combination of ga and pso for feature selection,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T10:19:21.913638Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation ab141a2a-b14b-43c7-abaf-8c5ec26370c7 · outbound

This paper cites Selective oppo- sition based grey wolf optimization,.

FeatureCuts: Feature Selection for Large Data by Optimizing the Cutoff Selective oppo- sition based grey wolf optimization,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T10:19:21.623396Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation be417847-231b-479b-a748-d238370dc281 · outbound

This paper cites Embedded chaotic whale survival algorithm for filter–wrapper feature selection,.

FeatureCuts: Feature Selection for Large Data by Optimizing the Cutoff Embedded chaotic whale survival algorithm for filter–wrapper feature selection,

Reference 26

Resolution: verified exact; doi, observed 2026-08-06T10:19:15.853652Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 9669e854-3b2e-4818-93b6-5082679bd92a · outbound

This paper cites Feature selection using the sine cosine algorithm,.

FeatureCuts: Feature Selection for Large Data by Optimizing the Cutoff Feature selection using the sine cosine algorithm,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T10:19:21.293124Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 31ea68a2-7b03-4458-81a0-48ec7640c4bc · outbound

This paper cites The uci machine learning repository,.

FeatureCuts: Feature Selection for Large Data by Optimizing the Cutoff The uci machine learning repository,

Reference 28

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 00e994a6-70cc-400c-b2ed-117899bbc373 · outbound

This paper cites Kaggle: Your machine learning and data science community,.

FeatureCuts: Feature Selection for Large Data by Optimizing the Cutoff Kaggle: Your machine learning and data science community,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T10:19:20.779212Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation f9c70fc8-ee80-47fd-9cfc-2d9a2794e8c9 · outbound

This paper cites Airline Dataset — kaggle.com,.

FeatureCuts: Feature Selection for Large Data by Optimizing the Cutoff Airline Dataset — kaggle.com,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T10:19:20.426637Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation d2a27481-1858-4395-adc7-ccd5654104d0 · outbound

This paper cites News Articles — kaggle.com,.

FeatureCuts: Feature Selection for Large Data by Optimizing the Cutoff News Articles — kaggle.com,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T10:19:20.147937Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 67442434-fa87-4762-ac4e-33ac78d5ed01 · outbound

This paper cites BlogFeedback,.

FeatureCuts: Feature Selection for Large Data by Optimizing the Cutoff BlogFeedback,

Reference 32

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Source-reported events for the cited work

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Observation ea56e7bc-7833-49d2-8ff5-a8291751cc75 · outbound

This paper cites CARER: Contextualized affect representations for emotion recognition,.

FeatureCuts: Feature Selection for Large Data by Optimizing the Cutoff CARER: Contextualized affect representations for emotion recognition,

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T10:19:19.876088Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 5eb2d100-a1d3-451e-98ac-804fa99e6eb1 · outbound

This paper cites Markov blanket-embedded genetic algorithm for gene selection,.

FeatureCuts: Feature Selection for Large Data by Optimizing the Cutoff Markov blanket-embedded genetic algorithm for gene selection,

Reference 34

Resolution: verified exact; doi, observed 2026-08-06T10:19:15.565390Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation e20d5cf5-bc23-47f7-a181-c1066f630e93 · outbound

This paper cites Sosnet: A graph convolutional network approach to fine-grained cyberbullying detection,.

FeatureCuts: Feature Selection for Large Data by Optimizing the Cutoff Sosnet: A graph convolutional network approach to fine-grained cyberbullying detection,

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T10:19:19.543997Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 1195c997-d777-4c6f-a6be-e7231fe73fca · outbound

This paper cites Gisette,.

FeatureCuts: Feature Selection for Large Data by Optimizing the Cutoff Gisette,

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-06T10:19:13.730868Z

Source-reported events for the cited work

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Observation 7d092b6d-a2f8-47ac-835d-331a1511b2e6 · outbound

This paper cites House prices - advanced regression techniques,.

FeatureCuts: Feature Selection for Large Data by Optimizing the Cutoff House prices - advanced regression techniques,

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T10:19:19.262818Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 5c39fe4b-cffd-419e-a837-aa5290ea7828 · outbound

This paper cites Cole and M.

FeatureCuts: Feature Selection for Large Data by Optimizing the Cutoff Cole and M

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-06T10:19:14.024316Z

Source-reported events for the cited work

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Observation 8133d214-e0de-4838-96b6-de66c0ece573 · outbound

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FeatureCuts: Feature Selection for Large Data by Optimizing the Cutoff Madelon,

Reference 39

Resolution: verified exact; doi, observed 2026-08-06T10:19:15.252719Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 555d2024-2edb-4f6b-bfec-66960280e9d9 · outbound

This paper cites MNIST Dataset — kaggle.com,.

FeatureCuts: Feature Selection for Large Data by Optimizing the Cutoff MNIST Dataset — kaggle.com,

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T10:19:18.949471Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 2c6fb32e-6d3b-4e1f-9621-9a9f93820bf2 · outbound

This paper cites Newsweeder: Learning to filter netnews,.

FeatureCuts: Feature Selection for Large Data by Optimizing the Cutoff Newsweeder: Learning to filter netnews,

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T10:19:18.649080Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 4e8dd7e2-9493-4d77-bcc1-cd83ed92414f · outbound

This paper cites 190k+ spam — ham email dataset for classifi- cation,.

FeatureCuts: Feature Selection for Large Data by Optimizing the Cutoff 190k+ spam — ham email dataset for classifi- cation,

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T10:19:18.315841Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 104544ed-7e43-4196-a3e3-0e152e622a98 · outbound

This paper cites Feature selection with the boruta package,.

FeatureCuts: Feature Selection for Large Data by Optimizing the Cutoff Feature selection with the boruta package,

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T10:19:18.016842Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 365e0b3c-5e7c-44c4-9e02-3b201ff5392e · outbound

This paper cites Benchmarking Relief-Based Feature Selection Methods for Bioinformatics Data Mining.

FeatureCuts: Feature Selection for Large Data by Optimizing the Cutoff Benchmarking Relief-Based Feature Selection Methods for Bioinformatics Data Mining

Reference 44

Resolution: verified exact; local_arxiv, observed 2026-08-06T10:19:17.577030Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Pith citing papers

Observation e790c7db-0663-4456-b4e9-055f60c5e1dd · inbound

FinKario: Event-Enhanced Automated Construction of Financial Knowledge Graph cites this paper.

FinKario: Event-Enhanced Automated Construction of Financial Knowledge Graph FeatureCuts: Feature Selection for Large Data by Optimizing the Cutoff

Reference 1

Resolution: verified exact; local_arxiv, observed 2026-08-06T10:03:23.187471Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.