David Buttler
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View article: MaTableGPT: GPT‐Based Table Data Extractor from Materials Science Literature (Adv. Sci. 16/2025)
MaTableGPT: GPT‐Based Table Data Extractor from Materials Science Literature (Adv. Sci. 16/2025) Open
GPT‐Based Table Data Extractor
View article: MaTableGPT: GPT‐Based Table Data Extractor from Materials Science Literature
MaTableGPT: GPT‐Based Table Data Extractor from Materials Science Literature Open
Efficiently extracting data from tables in the scientific literature is pivotal for building large‐scale databases. However, the tables reported in materials science papers exist in highly diverse forms; thus, rule‐based extractions are an…
View article: MaTableGPT: GPT-based Table Data Extractor from Materials Science Literature
MaTableGPT: GPT-based Table Data Extractor from Materials Science Literature Open
Efficiently extracting data from tables in the scientific literature is pivotal for building large-scale databases. However, the tables reported in materials science papers exist in highly diverse forms; thus, rule-based extractions are an…
View article: Deep learning of electrochemical CO<sub>2</sub> conversion literature reveals research trends and directions
Deep learning of electrochemical CO<sub>2</sub> conversion literature reveals research trends and directions Open
Machine learning (ML)-based protocol for selecting highly relevant papers, extracting important experimental data, and analyzing research trends & directions focusing on the field of CO 2 reduction reactions (CO 2 RRs).
View article: Information Extraction from Unstructured Text for the Biodefense Knowledge Center
Information Extraction from Unstructured Text for the Biodefense Knowledge Center Open
The Bio-Encyclopedia at the Biodefense Knowledge Center (BKC) is being constructed to allow an early detection of emerging biological threats to homeland security. It requires highly structured information extracted from variety of data so…
View article: Nanomaterial Synthesis Insights from Machine Learning of Scientific Articles by Extracting, Structuring, and Visualizing Knowledge
Nanomaterial Synthesis Insights from Machine Learning of Scientific Articles by Extracting, Structuring, and Visualizing Knowledge Open
Nanomaterials of varying compositions and morphologies are of interest for many applications from catalysis to optics, but the synthesis of nanomaterials and their scale-up are most often time-consuming and Edisonian processes. Information…
View article: Nanomaterials Synthesis Insights from Machine Learning of Scientific Articles by Extracting, Structuring, and Visualizing Knowledge
Nanomaterials Synthesis Insights from Machine Learning of Scientific Articles by Extracting, Structuring, and Visualizing Knowledge Open
Nanomaterials of varying compositions and morphologies are of interest for many applications from catalysis to optics, but the synthesis of nanomaterials and their scale-up are most often time-consuming and Edisonian processes. Information…
View article: Nanomaterials Synthesis Insights from Machine Learning of Scientific Articles by Extracting, Structuring, and Visualizing Knowledge
Nanomaterials Synthesis Insights from Machine Learning of Scientific Articles by Extracting, Structuring, and Visualizing Knowledge Open
Nanomaterials of varying compositions and morphologies are of interest for many applications from catalysis to optics, but the synthesis of nanomaterials and their scale-up are most often time-consuming and Edisonian processes. Information…
View article: Pipelines for Procedural Information Extraction from Scientific Literature: Towards Recipes using Machine Learning and Data Science
Pipelines for Procedural Information Extraction from Scientific Literature: Towards Recipes using Machine Learning and Data Science Open
This paper describes a machine learning and data science pipeline for\nstructured information extraction from documents, implemented as a suite of\nopen-source tools and extensions to existing tools. It centers around a\nmethodology for ex…