Two Six Labs, LLC

James Gentile

Chae A Clark

Ben Gelman

Simon Cho

Reed Gordon-Sarney

An extractive summarization model provides extraction and classification of research assertions, or claims, made by a documented body of research such as a scientific paper or article. Modern electronic publication and dissemination allows tremendous capability for researching and scrutinizing previous documented efforts for further research and study. Accordingly, a substantial volume of material is easily obtained in response to research efforts. The extractive summarization model provides a summarization of this scientific literature by identifying and classifying asserted claims made by a particular research document. Researchers may quickly identify relevant documents based on the extracted claims asserted by the document, facilitating substantive review.

Multi-stage narrative analysis

A machine learning approach for evaluating the replicability of research receives a scholarly paper or publication about a research effort, and applies learning models and natural language processing (NLP) to identify replicability of the asserted results. Rule based and machine learning approaches employ models based on preexisting research papers having defined replicability, and compares language features, research parameters and factual assertions extracted from a research paper for evaluation. A pipeline of evaluations and feature extraction analyzes the content of the research paper and renders a prediction value that the described research can be repeated with similar results.

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James Gentile