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10.1038/s41597-021-00839-5 http://scihub22266oqcxt.onion/10.1038/s41597-021-00839-5 33574342!7878896!33574342     free     free     free Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Sci+Data 2021 ; 8 (1): 59 Nephropedia Template TP {{tp|p=33574342|t=2021. The Zoltar forecast archive, a tool to standardize and store interdisciplinary prediction research |pdf=|usr=}}{{33574342}} gab.com Text The Zoltar forecast archive, a tool to standardize and store interdisciplinary prediction research JO: Sci Data http://www.kidney.de/pget.php?&tw=1&pmid=33574342 #FOAvip Forecasting has emerged as an important component of informed, data-driven decision-making in a wide array of fields. We introduce a new data model for probabilistic predictions that encompasses a wide range of forecasting settings. This framework clearly defines the constituent parts of a probabilistic forecast and proposes one approach for representing these data elements. The data model is implemented in Zoltar, a new software application that stores forecasts using the data model and provides standardized API access to the data. In one real-time case study, an instance of the Zoltar web application was used to store, provide access to, and evaluate real-time forecast data on the order of 10(8) rows, provided by over 40 international research teams from academia and industry making forecasts of the COVID-19 outbreak in the US. Tools and data infrastructure for probabilistic forecasts, such as those introduced here, will play an increasingly important role in ensuring that future forecasting research adheres to a strict set of rigorous and reproducible standards. Twit Text FOAVip The Zoltar forecast archive, a tool to standardize and store interdisciplinary prediction research ????Sci Data http://www.kidney.de/pget.php?&tw=1&pmid=33574342 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=33574342 #FOAvip English Wikipedia <ref>{{Cite pmid|33574342}}</ref> The Zoltar forecast archive, a tool to standardize and store interdisciplinary prediction research #MMPMID33574342 Reich NG; Cornell M; Ray EL; House K; Le K Sci Data 2021[Feb]; 8 (1): 59 PMID33574342show ga Forecasting has emerged as an important component of informed, data-driven decision-making in a wide array of fields. We introduce a new data model for probabilistic predictions that encompasses a wide range of forecasting settings. This framework clearly defines the constituent parts of a probabilistic forecast and proposes one approach for representing these data elements. The data model is implemented in Zoltar, a new software application that stores forecasts using the data model and provides standardized API access to the data. In one real-time case study, an instance of the Zoltar web application was used to store, provide access to, and evaluate real-time forecast data on the order of 10(8) rows, provided by over 40 international research teams from academia and industry making forecasts of the COVID-19 outbreak in the US. Tools and data infrastructure for probabilistic forecasts, such as those introduced here, will play an increasingly important role in ensuring that future forecasting research adheres to a strict set of rigorous and reproducible standards. |*Software[MESH] |COVID-19/epidemiology[MESH] |Datasets as Topic[MESH] |Disease Outbreaks[MESH] |Forecasting/*methods[MESH] |Humans[MESH]The Zoltar forecast archive, a tool to standardize and store interdisc(epmc).pdf DeepDyve Pubget Overpricing