FIGS_ICBW_StemRust_2017
<|begin_of_text|><|start_header_id|>system<|end_header_id|> You are a research archivist expert in dataset metadata. Answer the question truthfully.  <|eot_id|><|start_header_id|>user<|end_header_id|> Here is the Description of a dataset. Description:'The FIGSICBWStemRust2017 FIGS set was constructed using evaluation data from more than 5000 bread wheat accessions in Yemen during 2008 and machine learning algorithms including Random Forest, support vector machine and kernel nearest neighbors, and using WorldClim data. The metrics from the machine learning were high (Accuracy = 0.82 and Kappa = 0.58). 210 accessions were then selected based on higher predictive probability. FIGSICBWStemRust2017 is the name of the FIGS subset including the crop, trait name and the year of construction' . Please return only a json list of at most 3 Keywords corresponding to the Description:.<|eot_id|><|start_header_id|>assistant<|end_header_id|> {"Answer" : ["no poverty","stem rust","wheat","zero hunger"]} <|eot_id|>
 Here is the Description of a dataset. Description:'The FIGSICBWStemRust2017 FIGS set was constructed using evaluation data from more than 5000 bread wheat accessions in Yemen during 2008 and machine learning algorithms including Random Forest, support vector machine and kernel nearest neighbors, and using WorldClim data. The metrics from the machine learning were high (Accuracy = 0.82 and Kappa = 0.58). 210 accessions were then selected based on higher predictive probability. FIGSICBWStemRust2017 is the name of the FIGS subset including the crop, trait name and the year of construction' . Please return only a json list of at most 3 Keywords corresponding to the Description:.
The FIGSICBWStemRust2017 FIGS set was constructed using evaluation data from more than 5000 bread wheat accessions in Yemen during 2008 and machine learning algorithms including Random Forest, support vector machine and kernel nearest neighbors, and using WorldClim data. The metrics from the machine learning were high (Accuracy = 0.82 and Kappa = 0.58). 210 accessions were then selected based on higher predictive probability. FIGSICBWStemRust2017 is the name of the FIGS subset including the crop, trait name and the year of construction
no poverty; stem rust; wheat; zero hunger