Supplemental Material: Methane seeps as refugia during ash falls in the Late Cretaceous Western Interior Seaway of North America

Additional information on sample collection and stratigraphy of the site, faunal analysis and data standardization, and stable isotope analysis, and supplemental tables of raw and transformed datasets.<br>

Supplemental Material: Methane seeps as refugia during ash falls in the Late Cretaceous Western Interior Seaway of North America

Additional information on sample collection and stratigraphy of the site, faunal analysis and data standardization, and stable isotope analysis, and supplemental tables of raw and transformed datasets.<br>

Supplemental Material: Quantifying metasomatic high-field-strength and rare-earth element transport from alkaline magmas

Petrographic information, parameterization of the Grant model, description of the HFSE tonnage estimation method, and supplemental tables of whole-rock data, standardization, and HFSE volume-tonnage calculations.<br>

Supplemental Material: Quantifying metasomatic high-field-strength and rare-earth element transport from alkaline magmas

Petrographic information, parameterization of the Grant model, description of the HFSE tonnage estimation method, and supplemental tables of whole-rock data, standardization, and HFSE volume-tonnage calculations.<br>

A New Early Rumor Detection Model Based on BiGRU Neural Network

With the progress of society and the rapid development of computer technology, rumors arise on social media, which seriously affects the social economy. How to detect rumors accurately and rapidly has become one hot research topic. In this paper, a new early rumor detection model is proposed. The aim of this model is to increase the efficiency and the accuracy of rumor detection simultaneously. Specifically, in this model, the input data is firstly refined through account filtering and data standardization, then the BiGRU is used to consider the context relationship, and a reinforcement learning algorithm is applied to detection. Experimental results show that compared with other early rumor detection models (e.g., checkpoints), the accuracy of the proposed model is improved by 0.5% with the same speed, which testifies the effectiveness of this model.

DecTree v1.0 – chemistry speedup in reactive transport simulations: purely data-driven and physics-based surrogates

The computational costs associated with coupled reactive transport simulations are mostly due to the chemical subsystem: replacing it with a pre-trained statistical surrogate is a promising strategy to achieve decisive speedups at the price of small accuracy losses and thus to extend the scale of problems which can be handled. We introduce a hierarchical coupling scheme in which “full-physics” equation-based geochemical simulations are partially replaced by surrogates. Errors in mass balance resulting from multivariate surrogate predictions effectively assess the accuracy of multivariate regressions at runtime: inaccurate surrogate predictions are rejected and the more expensive equation-based simulations are run instead. Gradient boosting regressors such as XGBoost, not requiring data standardization and being able to handle Tweedie distributions, proved to be a suitable emulator. Finally, we devise a surrogate approach based on geochemical knowledge, which overcomes the issue of robustness when encountering previously unseen data and which can serve as a basis for further development of hybrid physics–AI modelling.

Data Management and Interactive Visualizations for the Evolving Marine Biodiversity Observation Network

Assessing the current state of and predicting change in the ocean’s biological and ecosystem resources requires observations and research to safeguard these valuable public assets. The Marine Biodiversity Observation Network (MBON) partnered with the Global Ocean Observing System Biology and Ecosystems Panel and the Ocean Biodiversity Information System to address these needs through collaboration, data standardization, and data sharing. Here, we describe the generalized MBON data processing flow, which includes several steps to ensure that data are findable, accessible, interoperable, and reusable. By following this flow, data collected and managed by MBON have contributed to our understanding of the Global Ocean Observing System Essential Ocean Variables and demonstrated the value of web-based, interactive tools to explore and better understand environmental change. Although the MBON’s generalized data processing flow is already in practice, work remains in building ontologies for biological concepts, improving processing scripts for data standardization, and speeding up the data collection-to-sharing timeframe.