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bagbert

Code for BERT-based bagging-stacking for multi-topic classification

bootstrap3

OJS custom Opscidia bootstrap theme based on a community built theme for OJS 3 that implements Bootstrap 3 components

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

grobid

A machine learning software for extracting information from scholarly documents

mtft_zsl

Source code for the EMNLP Findings paper, "Towards Zero-Shot Conditional Summarization with Adaptive Multi-Task Fine-Tuning"

ojs

OJS (Open Journal Systems) Opscidia fork

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.

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

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)