Pinned Repositories
Bagbert
Code for BERT-based bagging-stacking for multi-topic classification
connectors
Source code for all Elastic connectors, developed by the Search team at Elastic, and home of our Python connector development framework
django-organizations
:couple: Multi-user accounts for Django projects
mtft_zsl
Source code for the EMNLP Findings paper, "Towards Zero-Shot Conditional Summarization with Adaptive Multi-Task Fine-Tuning"
opscidia-api-docs
opscidia-custom-theme
This is a custom theme for the latest OJS 3.1.2.4 release, based on the community-built theme for OJS 3+ that implements Bootstrap 3 components and the Old Gregg Theme for OJS 3 that uses JATS Parser Plugin for automatic rendering of articles in JATS XML format and displaying them on article landing page.
pkp-lib
OJS / PKP Web Application Library (Opscidia fork)
saber
Saber is a deep-learning based tool for information extraction in the biomedical domain. Pull requests are welcome! Note: this is a work in progress. Many things are broken, and the codebase is not stable.
science-checker
The present project, called Opscidia Science Checker, aims at developing a tool to verify scientific claims by analyzing the pertinent and available scientific literature. The subject of fake news is a very topical one. With social networks, and the advances of artificial intelligence, it is easier and easier to create fake news, and they circulate quicker and quicker. Health is a particularly nasty topic for fake news. Scam medicine, and worrisome information circulate, often based on absolutely no scientific evidence.. The main idea of this project is to build several indicators based on the analysis of very large volumes of scientific articles. These indicators will be easy to understand in order for the non-specialist to have a quick idea of whether an information is backed by the scientific literature, is under debate, or is totally groundless. The tool developed will be of use for journalists and media groups as well as for the general public. The idea actually emerged after a discussion with a scientific journalist who conducts long investigations on cases of possible fake medicine. The use of tools such as ours would be very useful to help them target the topics that deserve investigation, and would give a starting point for their work. We have further discussed this topic with several other journalists that all showed a very strong interest for the development of such a product.
scispacy-ops
A full spaCy pipeline and models for scientific/biomedical documents. (Opscidia fork for Python 3.11 and 3.12)
Opscidia's Repositories
opscidia/Bagbert
Code for BERT-based bagging-stacking for multi-topic classification
opscidia/science-checker
The present project, called Opscidia Science Checker, aims at developing a tool to verify scientific claims by analyzing the pertinent and available scientific literature. The subject of fake news is a very topical one. With social networks, and the advances of artificial intelligence, it is easier and easier to create fake news, and they circulate quicker and quicker. Health is a particularly nasty topic for fake news. Scam medicine, and worrisome information circulate, often based on absolutely no scientific evidence.. The main idea of this project is to build several indicators based on the analysis of very large volumes of scientific articles. These indicators will be easy to understand in order for the non-specialist to have a quick idea of whether an information is backed by the scientific literature, is under debate, or is totally groundless. The tool developed will be of use for journalists and media groups as well as for the general public. The idea actually emerged after a discussion with a scientific journalist who conducts long investigations on cases of possible fake medicine. The use of tools such as ours would be very useful to help them target the topics that deserve investigation, and would give a starting point for their work. We have further discussed this topic with several other journalists that all showed a very strong interest for the development of such a product.
opscidia/bootstrap3
OJS custom Opscidia bootstrap theme based on a community built theme for OJS 3 that implements Bootstrap 3 components
opscidia/connectors
Source code for all Elastic connectors, developed by the Search team at Elastic, and home of our Python connector development framework
opscidia/django-organizations
:couple: Multi-user accounts for Django projects
opscidia/grobid
A machine learning software for extracting information from scholarly documents
opscidia/mtft_zsl
Source code for the EMNLP Findings paper, "Towards Zero-Shot Conditional Summarization with Adaptive Multi-Task Fine-Tuning"
opscidia/ojs
OJS (Open Journal Systems) Opscidia fork
opscidia/opscidia-api-docs
opscidia/opscidia-custom-theme
This is a custom theme for the latest OJS 3.1.2.4 release, based on the community-built theme for OJS 3+ that implements Bootstrap 3 components and the Old Gregg Theme for OJS 3 that uses JATS Parser Plugin for automatic rendering of articles in JATS XML format and displaying them on article landing page.
opscidia/Opscidia-JATS-Convergencias
OJS code for the latest OJS 3.2.1.4 release, to fix some bugs with JATS Parser and Texture plugins for automatic rendering of articles in JATS XML format and displaying them on article landing page. Also hosted journals stylesheets
opscidia/pkp-lib
OJS / PKP Web Application Library (Opscidia fork)
opscidia/saber
Saber is a deep-learning based tool for information extraction in the biomedical domain. Pull requests are welcome! Note: this is a work in progress. Many things are broken, and the codebase is not stable.
opscidia/scispacy-ops
A full spaCy pipeline and models for scientific/biomedical documents. (Opscidia fork for Python 3.11 and 3.12)