ArticleFood chemistry: X2025
Machine learning model interpretability using SHAP values: Applied to the task of classifying and predicting the nutritional content of different cuts of mutton.
Article in Food chemistry: X, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
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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.
The trial behind it
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Who cites it
8 citing papers in PubMed.
- Machine learning for identifying antibacterial agents derived from yam (Food chemistry: X · 2026Article
- AI-Driven Nondestructive Measurement Technologies for Meat Quality and Safety: A Review.Foods (Basel, Switzerland) · 2026Review
- Integrating Machine Learning and Expert Sensory Evaluation to Identify Key Drivers of Tomato Fruit Quality: A Multi-Model and Age-Stratified Analysis.Foods (Basel, Switzerland) · 2026Article
- Yeast culture promotes butyrate produced fibrolytic bacteria as intracellular hydrogen sink in the rumen.Microbiome · 2026Article
- Machine learning predicts ICU mortality in cardiogenic shock: interpreting SOFA, lactate, and pH thresholds.BMC cardiovascular disorders · 2026Article
- Hybrid near-infrared and chemical-based machine learning enhances the reliability of chili powder origin classification.Scientific reports · 2026Article
- Multimodal AI for Real-Time Food Safety and Quality: From Sensors to Foundation Models, Edge Deployment, and Regulation.Food science & nutrition · 2026Review
- CABNas-nir: A near-infrared classification for urban pipe network sludge on the fusion algorithm of NAS framework and active learning.PloS one · 2025Article
Corrections and comments
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Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The rapid identification and prediction of nutritional components in fresh meat products pose a significant challenge. This study aims to classify different cuts of fresh mutton and predict their nutritional components using SVM and PLS model, focusing on the differences in fatty acid composition among the
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Registered trials
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.