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        <identifier>oai:figshare.com:article/33742555</identifier>
        <datestamp>2026-09-14T14:21:45Z</datestamp>
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          <dc:title>Model-level dataset from a quantitative review of XRF-based soil property prediction and data-fusion approaches</dc:title>
          <dc:creator>Vinicius Pires Rezende (20398475)</dc:creator>
          <dc:subject>Agricultural management of nutrients</dc:subject>
          <dc:subject>XRF</dc:subject>
          <dc:subject>sensor fusion</dc:subject>
          <dc:subject>soil fertility</dc:subject>
          <dc:subject>proximal sensing</dc:subject>
          <dc:subject>machine learning</dc:subject>
          <dc:description>&lt;p dir="ltr"&gt;This dataset contains the model-level database used in a quantitative review of XRF-based soil property prediction models and data-fusion approaches. The database was compiled from peer-reviewed studies published between 2012 and 2026. Each row represents one predictive model entry rather than one unique article.&lt;/p&gt;&lt;p dir="ltr"&gt;The dataset includes information on the target soil attribute, sensor configuration, data-fusion level, fusion implementation strategy, modeling algorithm, preprocessing method, experimental environment, geographical scope, sample size, country, climate classification, soil texture information, and model performance metrics. The main performance metrics include R², RMSE, RPD, and RPIQ when reported in the original studies.&lt;/p&gt;&lt;p dir="ltr"&gt;Sensor configurations were classified as XRF-only when the predictive model used only XRF-derived variables and as data fusion when XRF was combined with at least one additional source of information. Data-fusion approaches were harmonized into three main levels according to the stage at which information was integrated: low-level, mid-level, and high-level fusion. Feature-level and score-level approaches were grouped as mid-level fusion, whereas decision-level and ensemble-level approaches were grouped as high-level fusion.&lt;/p&gt;&lt;p dir="ltr"&gt;The dataset supports the analyses, figures, and tables presented in the associated review manuscript on XRF-based soil property prediction and data-fusion strategies. The value of n reported in the manuscript refers to the number of model-level entries, not the number of unique articles.&lt;/p&gt;</dc:description>
          <dc:date>2026-09-14T14:21:45Z</dc:date>
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          <dc:identifier>10.6084/m9.figshare.33742555.v1</dc:identifier>
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          <dc:rights>CC BY 4.0</dc:rights>
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