Evidence map›Paper›PMID 42617252›Full record

ArticlePoultry science2026

Physics‑informed machine learning modeling with dual SHAP analysis for predicting Salmonella Enteritidis growth on chicken meat treated with slightly acidic electrolyzed water.

Yunxiang Zhu, Shan Bing, Yitian Zang, Yanjiao Li, Guoping Wu, Guosheng Zhang, Nengshui Ding, Guoyun Wu, Zhen Wang, Ruilin Wang and 6 more

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In one paragraph

Article in Poultry science, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
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0citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

16 authors.

Yunxiang ZhuJiangxi Agricultural University, Jiangxi, 330045, China.
Shan BingJiangxi Agricultural University, Jiangxi, 330045, China.
Yitian ZangJiangxi Agricultural University, Jiangxi, 330045, China. Electronic address: zangyitian1@126.com.
Yanjiao LiJiangxi Agricultural University, Jiangxi, 330045, China.
Guoping WuJiangxi Agricultural University, Jiangxi, 330045, China.
Guosheng ZhangJiangxi Agricultural Technology Extension Center, Jiangxi, 330046, China.
Nengshui DingJiangxi Agricultural University, Jiangxi, 330045, China.
Guoyun WuJiangxi Agricultural University, Jiangxi, 330045, China.
Zhen WangJiangxi Agricultural University, Jiangxi, 330045, China.
Ruilin WangJiangxi Agricultural University, Jiangxi, 330045, China.
Fule YangJiangxi Agricultural University, Jiangxi, 330045, China.
Yucheng ZhangJiangxi Agricultural University, Jiangxi, 330045, China.
Lili XiaoJiangxi Agricultural University, Jiangxi, 330045, China.
Chenxi CuiJiangxi Agricultural University, Jiangxi, 330045, China.
Yuhang MaJiangxi Agricultural University, Jiangxi, 330045, China.
Hongxin FuJiangxi Agricultural University, Jiangxi, 330045, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Slightly acidic electrolyzed water (SAEW) is an effective sanitizer for controlling Salmonella Enteritidis in chicken processing, but existing mechanistic models suffer from systematic prediction bias due to structural simplifications, limiting its precise application under complex temperature scenarios. To address this bias, we developed a SGompertz-CatBoost residual-correction hybrid model and conducted dual SHAP analyses to diagnose bias sources and interpret decision mechanisms. The hybrid model achieved an R

Indexed as

Physics-informed machine learningResidual correctionSalmonella EnteritidisSHAPSlightly acidic electrolyzed water

Identifiers

PMID42617252
PMCPMC13521231

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.