ChatGPT's advice is perceived as better than that of professional advice columnists.

ChatGPT is a high-performance large language model that has the potential to significantly improve human-computer interactions. It can provide advice on a range of topics, but it is unclear how good this advice is relative to that provided by competent humans, especially in situations where empathy is required. Here, we report the first investigation of whether ChatGPT's responses are perceived as better than those of humans in a task where humans were attempting to be empathetic.

DualGCN: Exploring Syntactic and Semantic Information for Aspect-Based Sentiment Analysis.

The task of aspect-based sentiment analysis aims to identify sentiment polarities of given aspects in a sentence. Recent advances have demonstrated the advantage of incorporating the syntactic dependency structure with graph convolutional networks (GCNs). However, their performance of these GCN-based methods largely depends on the dependency parsers, which would produce diverse parsing results for a sentence.

Automated detection of discourse segment and experimental types from the text of cancer pathway results sections.

Automated machine-reading biocuration systems typically use sentence-by-sentence information extraction to construct meaning representations for use by curators. This does not directly reflect the typical discourse structure used by scientists to construct an argument from the experimental data available within a article, and is therefore less likely to correspond to representations typically used in biomedical informatics systems (let alone to the mental models that scientists have). In this study, we develop Natural Language Processing methods to locate, extract, and classify the individual passages of text from articles' Results sections that refer to experimental data.

Scoring Coreference Partitions of Predicted Mentions: A Reference Implementation.

The definitions of two coreference scoring metrics- B and CEAF-are underspecified with respect to , as opposed to (or ) mentions. Several variations have been proposed that manipulate either, or both, the key and predicted mentions in order to get a one-to-one mapping. On the other hand, the metric BLANC was, until recently, limited to scoring partitions of key mentions.

An Extension of BLANC to System Mentions.

BLANC is a link-based coreference evaluation metric for measuring the quality of coreference systems on gold mentions. This paper extends the original BLANC ("BLANC-gold" henceforth) to system mentions, removing the gold mention assumption. The proposed BLANC falls back seamlessly to the original one if system mentions are identical to gold mentions, and it is shown to strongly correlate with existing metrics on the 2011 and 2012 CoNLL data.

Layout-aware text extraction from full-text PDF of scientific articles.

Background: The Portable Document Format (PDF) is the most commonly used file format for online scientific publications. The absence of effective means to extract text from these PDF files in a layout-aware manner presents a significant challenge for developers of biomedical text mining or biocuration informatics systems that use published literature as an information source. In this paper we introduce the 'Layout-Aware PDF Text Extraction' (LA-PDFText) system to facilitate accurate extraction of text from PDF files of research articles for use in text mining applications.

Knowledge engineering tools for reasoning with scientific observations and interpretations: a neural connectivity use case.

Background: We address the goal of curating observations from published experiments in a generalizable form; reasoning over these observations to generate interpretations and then querying this interpreted knowledge to supply the supporting evidence. We present web-application software as part of the 'BioScholar' project (R01-GM083871) that fully instantiates this process for a well-defined domain: using tract-tracing experiments to study the neural connectivity of the rat brain.

Results: The main contribution of this work is to provide the first instantiation of a knowledge representation for experimental observations called 'Knowledge Engineering from Experimental Design' (KEfED) based on experimental variables and their interdependencies.

Indigenous message tailoring increases consumption of fresh vegetables by clients of community pantries.

This study tested whether message tailoring of recipes and food-use tips for low-income households is superior to providing a generic version of the material. The field experiment was conducted in the busy conditions found at community food pantries, and included 10 food distributions at each of six sites. We analyzed the consumption of fresh vegetables 6 days following distributions, and retention of print materials 6 weeks later.

The Future of Research Communication.

This report documents the program and the outcomes of Dagstuhl Perspectives Workshop 11331 "The Future of Research Communication". The purpose of the workshop was to bring together researchers from these different disciplines, whose core research goal is changing the formats, standards, and means by which we communicate science.