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Validation results of Non-parametric models of pH Neutralization plant Dataset

<p>This repository contains a table with different validation results of a series of models tested in pH Neutralization plant and Clarke plant.</p> <p>In this case, the naming protocol was as follows:&nbsp;[plant name]_DataSet_[model variable].</p> <p>The content of every CSV file is presented as follows:&nbsp;</p> <p>Column 1: { name: Model_No, type: numeric integer, limit: None, description: Code to identifiy the model (Primary Key)}</p> <p>Column 2: { name: KS, type: numeric float, limits: [0 1], description: Kolgomorov-Smirnov test}</p> <p>Column 3: { name: AD, type: numeric float, limits: [0 1], description: Anderson-Darling test}</p> <p>Column 4: { name: SW, type: numeric float, limits: [0 1], description: Shapiro-Wilk test}</p> <p>Column 5: { name: WX, type: numeric float, limits: [0 1], description: Wilcoxon&nbsp;test}</p> <p>Column 6: { name: FIT, type: numeric float, limits: [-Inf&nbsp;1], description: Goodness of Fit metric}</p> <p>Column 7: { name: TIC, type: numeric float, limits: [0 1], description: Theil Inequality Index}</p> <p>Column 8: { name: Willmott, type: numeric float, limits: [0 1], description: Willmott metric}</p> <p>Column 9: { name: Russell_Pr, type: numeric float, limits: [0 1], description: Phase of Russell&nbsp; }</p> <p>Column 10: { name: Russell_Mr, type: numeric float, limits: [0 Inf], description: Magnitude of Russell&nbsp; }</p> <p>Column 11: { name: SG_Mr, type: numeric float, limits: [-Inf&nbsp;1], description: Sprague &amp; Geers}</p> <p>Column 12: { name: Anova, type: numeric float, limits: [0 1], description: Anova test}</p> <p>Column 13: { name: Dvure, type: numeric float, limits: [0 100], description: Dvurecenska metric}</p> <p>Column 14: { name: DTW, type: numeric float, limits: [0 Inf], description: DTW metric}</p> <p>Column 15: { name: D_DTW, type: numeric float, limits: [0 Inf], description: derivative of DTW metric}</p>

ShareScore

28/100

Overall dataset sharing score

Score breakdown

These five areas show where the dataset supports — or may limit — practical reuse.

Stewardship
8
Harmonization
4
Access
16
Reuse readiness
0
Engagement
0

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