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Software . 2024
License: CC BY
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chrisbanks/bTB-diagnostics: Version 2 for submission to PLOS CB

integration_instructionsResearch softwarekeyboard_double_arrow_right Software 12 Oct 2024Publisher:Zenodo
Authors: Chris Banks;
Code repository: https://github.com/chrisbanks/bTB-diagnostics/tree/sub.plos.cb

doi: 10.5281/zenodo.13923293 , 10.5281/zenodo.13923294 , 10.5281/zenodo.16886188

chrisbanks/bTB-diagnostics: Version 2 for submission to PLOS CB

Abstract

# bTB-diagnostics This project trains a Histogram Boosted Regression Tree model on data from Bovine Tuberculosis (bTB) testing and cattle herd metadata to predict the risk of bTB outbreak. This can be used to improve the herd-level sensitivity or specificity of the diagnostic test and also to analyse the risk factors involved in predicting bTB outbreaks. The project consists of a number of Jupyter Notebooks:(i) Data_Curation* -- processes the various input data into a matrix for model training.(ii) bTB-Diagnostic_2020_v4_crossVal+tuning* -- code that trains the various models.(iii) bTB-Diagnostic_2020_final_model* -- code that performs various analysis on the models.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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