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Pith Integrity · Reference Change Desk · events-only

Reference changes

See every place this corpus cites a work that was later retracted, corrected, withdrawn, or placed under expression of concern: exact quote, event source, and what happened next. No model judges the citation.

A notice on this page means a citing paper's bibliography includes a work with a published scholarly-record event. It is not a judgment on the citing paper.

Scoped to citing paper 2607.23482 · clear

01Events with corpus notices

02One-hop citation notices (secondary index)

Correction Crossref Open
Charging Phase Health Indicators for Battery State-of-Health Estimation: A Systematic Comparison of CC, CV, and Combined Approaches under Cross-Battery Validation

cites A quick on-line state of health estimation method for Li -ion battery with incremental capacity curves processed by Gaussian f ilter · ref [19] · event 2018-05-23 · 2607.23482 · event page · DOI 10.1016/j.jpowsour.2017.10.092

Raw extraction · bibliography line

Li Y , Abdel-Monem M, Gopalakrishnan R, Berecibar M, Nanini-Maury E, Omar N, Van den Bossche P, Van Mierlo J. A quick on-line state of health estimation method for Li -ion battery with incremental capacity curves processed by Gaussian f ilter. Journal of Power Sources 2018; 373: 40–53. https://doi.org/10.1016/j.jpowsour.2017.10.092

Parser render (TeX stripped for reading; raw above is the evidence)

Li Y, Abdel-Monem M, Gopalakrishnan R, Berecibar M, Nanini-Maury E, Omar N, Van den Bossche P, Van Mierlo J. A quick on-line state of health estimation method for Li -ion battery with incremental capacity curves processed by Gaussian f ilter. Journal of Power Sources 2018; 373: 40–53. https://doi.org/10.1016/j.jpowsour.2017.10.092

Correction Crossref Open
Charging Phase Health Indicators for Battery State-of-Health Estimation: A Systematic Comparison of CC, CV, and Combined Approaches under Cross-Battery Validation

cites Predicting the state of charge and health of batter ies using data-driven machine learni ng · ref [18] · event 2020-06-15 · 2607.23482 · event page · DOI 10.1038/s42256-020-0156-7

Raw extraction · bibliography line

Ng M F, Zhao J, Yan Q, Conduit G J, Seh Z W. Predicting the state of charge and health of batter ies using data-driven machine learni ng. Nature Machine Intelligence 2020; 2: 161–170. https://doi.org/10.1038/s42256-020-0156-7