1 to 10 of 250 Results
May 12, 2026
Lee, Yoo Young, 2026, "Python Code Designed for Subject Translation for SciFree's Journal Search Tool (JST)", https://doi.org/10.5683/SP3/TNANHJ, Borealis, V1, UNF:6:qgRVymIEzaAG88BavlI4lA== [fileUNF]
SciFree's Journal Search Tool (JST) enables researchers and authors to seach for journals that are part of University Libraries' Open Access agreements. The tool indicates the corresponding Article Processing Charge (APC) waiver or discount associated with each journal. Users may search by journal title, publisher, ISSN, or subject terms. Because s... |
Apr 15, 2026
Maredia, Nawal; Laurie, Cassandra; Ramsay, Tim; MacDonald, Shannon E.; McMillan, Jacqueline; Basta, Nicole E.; Fadel, Shaza A.; Andrew, Melissa K.; Wilson, Kumanan; Chyderiotis, Sandra; Elliott, Stephanie; Bouzanis, Katrina; Barratt, Jane; Sulis, Giorgia, 2026, "Supporting data for: Assessing knowledge, attitudes, willingness, and barriers to pneumococcal vaccination among Canadian older adults: a cross-sectional survey", https://doi.org/10.5683/SP3/AXHKHN, Borealis, V1
Pneumococcal disease is a leading cause of morbidity and mortality worldwide, with older adults aged 65 and above at particularly high risk for invasive pneumococcal infections. In Canada, pneumococcal vaccination has been recommended for this age group since 1989, yet coverage remains below national targets. Currently, only about 55% of older adul... |
Feb 5, 2026
Frize, Monique; Deschênes, Claire, 2026, "Supporting Data for: Women’s Contribution to Science and Technology through ICWES Conferences", https://doi.org/10.5683/SP3/LZJJLV, Borealis, V1, UNF:6:6sHlyQvXXqWMhYBDJYVKtA== [fileUNF]
This dataset was created by Monique Frize, Claire Deschênes and Ruby Heap from data collected on each International Conference of Women Engineers and Scientists (ICWES), from ICWES-I to ICWES-XII. The dataset was first archived with the University of Ottawa Archives and Special Collections and has since been transformed into a dataset for analyses... |
Nov 28, 2025
Conway, Kyle; Gramaccia, Julie Alice; Scholz, Nikita; Averbeck, Téana, 2025, "Replication data for: Measuring Lexical Distance between Parallel Corpora: The Case of AI-Generated News Translation", https://doi.org/10.5683/SP3/MFZTWZ, Borealis, V1, UNF:6:v93vHhRpGD/NphylJBCVww== [fileUNF]
Data and code (in R) corresponding to the article "Measuring Lexical Distance between Parallel Corpora: The Case of AI-Generated News Translation" The purpose of this project was to develop tools to measure statistical distance between corpora of translated news articles in English in French. Included here are the meta-data for the articles, gather... |
Oct 20, 2025
Liang, Lisha; Han, Lingfang; Dhuper, Misha; Lutek, Keegan; Standen, Emily, 2025, "Replication data for: Liang et al 2025. Walking elicits muscle functional changes in the pectoral fin of Polypterus senegalus. JEB", https://doi.org/10.5683/SP3/IGEDUL, Borealis, V1, UNF:6:bsw1eA5ZhnkN4yfTD0KUWw== [fileUNF]
This dataset contains all numerical data (electromyogrpahy and kinematics) and r-code required to replicate the analysis discussed in Liang et al. 2025. Walking elicits muscle functional change in the pectoral fin of Polypterus senegalus. doi:10.1242/jeb.250474. The r-code (Liang_etal_2025_RProject.Rproj and tidyLinearAnalysis.R) works in conjuncti... |
Oct 15, 2025
Abdoulkader, Nasteho; Archibald, Jennifer; Lignereux, Morgane; Lehoux, Eric A.; Catelas, Isabelle, 2025, "Replication Data for: NLRP3 inflammasome-dependent and -independent interleukin-1β release by macrophages exposed to wear and corrosion products from CoCrMo implants", https://doi.org/10.5683/SP3/IEBNOE, Borealis, V1
Wear particles and metal ions released from cobalt–chromium–molybdenum (CoCrMo) alloy implants present a significant clinical concern. Particles such as Cr2O3 and CoCrMo and metal ions, including Co2+ and Cr3+, have the potential to induce adverse local tissue reactions (ALTR) that can lead to implant failure. The pro-inflammatory response of macro... |
Sep 2, 2025
Zafar, Huma, 2025, "Replication data for: Examining the OpenAlex Concepts: A Detailed Case Study of Machine-Derived Classification", https://doi.org/10.5683/SP3/29QGMP, Borealis, V1
Machine-learning techniques are becoming increasingly popular in metadata and clas- sification work due to their ability to operate at scale, but insufficient consideration has been given to how effective such techniques truly are against traditional prac- tice. This dataset was generated as part of a thesis project to analyze the machine-generated... |
Jun 26, 2025
van Walsum, Saskia; Butler, Leigh-Ann; Hare, Madelaine; Ripp, Chantal; Haustein, Stefanie, 2025, "Environmental scan of Open science policies - Canada, globally and U15 institutions", https://doi.org/10.5683/SP3/NTFQPS, Borealis, V2, UNF:6:Xt46LQPw22NgyBpEcivHcA== [fileUNF]
This dataset includes the results of two environmental scanning activities to better understand existing open science practices across Canada and globally. The file titled "Scan of open science policies - Canada and globally" includes results of a scan of OS practices that were manually surveyed across 40 national and global institutions, organizat... |
Jun 24, 2025 - Fichiers de préservation de la Série de tutoriels sur l’apprentissage-machine = Preservation files for The Machine Learning Tutorial Series
Van der Kolk, Jarno; Darveau, Peter; Tayler, Felicity; Cheung, Melissa, 2025, "Plus proches voisins | K-nearest neighbours", https://doi.org/10.5683/SP3/BPE2VO, Borealis, V3, UNF:6:obcfTbACzjK4pOPXcosJjw== [fileUNF]
K-nearest neighbours (KNN) is a machine learning algorithm that is good a classifying moderately-sized datasets. It does so by looking at the n-dimensional space, where n is the number of features, and looking at nearby points to the data point you want to classify. It is a fairly simple technique but it can be very effective for data with low nois... |
Jun 24, 2025 - Fichiers de préservation de la Série de tutoriels sur l’apprentissage-machine = Preservation files for The Machine Learning Tutorial Series
Van der Kolk, Jarno; Darveau, Peter; Tayler, Felicity; Cheung, Melissa, 2025, "Traitement du langage naturel | Natural language processing", https://doi.org/10.5683/SP3/CER6YQ, Borealis, V4
Natural language processing (NLP) is a machine learning technique to analyze large amounts of text to extract information. Some examples are sentiment analysis, translation, transcription, summarizing, tagging, but NLP is a very broad term and can apply to anything text related. This tutorial consists of two notebooks. The first notebooks delves in... |
