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Record W4416965611 · doi:10.1109/tfuzz.2025.3613024

Corrections to “Robust Classification via Interval Type-2 Fuzzy C-Means and Gradient Boosting”

2025· article· W4416965611 on OpenAlexaff
Yunlong Zhu, Haibin Duan, Zheng Wang, Eun-Hu Kim, Zunwei Fu, Witold Pedrycz

Bibliographic record

VenueIEEE Transactions on Fuzzy Systems · 2025
Typearticle
Language
FieldComputer Science
TopicFuzzy Logic and Control Systems
Canadian institutionsUniversity of Alberta
FundersNatural Science Foundation of Shandong ProvinceNational Natural Science Foundation of China
KeywordsInterval (graph theory)Fuzzy logicFuzzy setFuzzy control systemFuzzy classificationPattern recognition (psychology)

Abstract

fetched live from OpenAlex

Original Article: Robust Classification via Interval Type-2 Fuzzy C-Means and Gradient Boosting, IEEE Transactions on Fuzzy Systems, vol. 33, no. 9, pp. 3103–3117, Sept. 2025. doi:10.1109/TFUZZ.2025.3583051.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.980
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.003
Science and technology studies0.0020.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.031
GPT teacher head0.250
Teacher spread0.218 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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