generated at previous steps, and adding daily through yearly temporal aggregations of most of the variables in the dataset and related quality flags. At this step, automated checks were performed on all the variables to ensure consistency, and the final files with all the contributed and derived ...
Article Open access 19 June 2024 Dramatic uneven urbanization of large cities throughout the world in recent decades Article Open access 23 October 2020 Global 30 meters spatiotemporal 3D urban expansion dataset from 1990 to 2010 Article Open access 26 May 2023 Introduction...
Note: I believe the dataset shuffling has a bug — the dataset is shuffled using the same seed for some reason (lm_human_preferences/lm_tasks.py#L94-L97). Reward Model Implementation Details In this section, we discuss reward-model-specific implementation details. We...
If you need more data to experiment with you can use any publicly available dataset and convert it to the format described above. For example, you can use a dataset provided by one of the Yandex challenges (you need to register to get access to the data): ...
I am trying to find a tidyverse-based programmatic approach to calculating the number of variables meeting a condition in a dataset. The data contains a row for each individual and a variable containing a code that describes something about that individual. I need to efficiently...
Kolmogorov-Smirnov and a Chi-Square bootstrap) to assess whether a given motif occurs uniformly in the promoter region of a gene. Using the test that performed better in this dataset, we proceeded to study the positional distribution of several well known cis-regulatory elements, in the promoter...
In this work, we aim to leverage the complex information available in a large reanalysis dataset via DA to provide estimates and assess the dynamics of important, physically-based parameters in the context of a reduced order model. 1.2. Data Assimilation and Reduced-Order Models Data assimilation...
I am attempting to use the functionsprep(), juice(), and bake()in order to generate the correct data objects for model predictions objects by following this tutorial below. Tutorial (see screenshots below) https://meghan.rbind.io/post/tidymodels-intro/ ...
The value of historic observational weather data for reconstructing long-term climate patterns and the detailed analysis of extreme weather events has long been recognized (Le Roy Ladurie, 1972; Lamb, 1977). In some regions however, observational data has not been kept regularly over time, or it...
Extreme heat is increasingly being acknowledged as a serious hazard to human health, through a combination of physiological responses to heat, expressed as dry and wet bulb temperatures, and personal factors. Here we present an analysis of the diurnal va