+ HEALTH Background Discharge letters are essential for continuity of care, yet patients often misunderstand their con…± HEALTH Hematoxylin and Eosin (H&E) glass slide preparation is fundamental to histopathology. Pathologists' expertise…+ CLIMATE Traditional soil heavy metal risk assessments suffer from fragmented indices and poor logical integration. Co…± HEALTH Background Neonatal pneumothorax can progress rapidly, yet detection on supine chest radiographs remains chal…+ HEALTH T cell exhaustion has widespread implications for the progression and treatment of chronic diseases including…+ HEALTH Background Standard pulmonary arterial hypertension (PAH) risk models may not fully apply to PAH associated w…+ HEALTH Objectives To map and synthesize the scientific evidence regarding the use of Augmented Reality (AR) and Mixe…± HEALTH Objective To examine whether the outputs of machine learning algorithms designed to predict risk of cardiovas…
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TRV-2026-1086Certified recordPeer-reviewed

Ecological risk zoning of soil heavy metal pollution using biomarker-enhanced indexing and machine learning

Traditional soil heavy metal risk assessments suffer from fragmented indices and poor logical integration. Compared to single-chemical indicators, biomarkers more sensitively reflect biological effects and early ecological risks. To address these issues, a method for constructing a comprehensive index integrating biological and non-biological multi-indexes was proposed in this study. First, the Criteria Importance Through Intercriteria Correlation (CRITIC)-Fuzzy Biomarker Response Index (CFBRI) is developed by i…

Climate · G Space — documented gain · certified 2026-09-14 · v1 · article view · machine-readable

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Machine learning-based risk zoning using integrated biological and abiotic indexes improved fit and classification, with CFBRI raising R2 to 0.62 and Random Forest models reaching cross-validation accuracies of 0.888 for agricultural land and 0.905 for construction land.

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Truvace Impact Record TRV-2026-1086, v1: “Ecological risk zoning of soil heavy metal pollution using biomarker-enhanced indexing and machine learning.” Truvace, 2026-09-14. /record/TRV-2026-1086 (accessed at citation time). sha256 c6ea82504ddec875…

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