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About Rep Data Rep Data provides full-service data collection solutions for primary researchers, helping expedite data collection for primary quantitative research studies with a hyper-focus on data ...
The ubiquitin-proteasome system contributes to protein quality control, involving E3 ligases that ubiquitinate proteins and leading to their degradation. The dysregulation of protein degradation ...
As consumers switch from Google search to ChatGPT, a new kind of bot is scraping data for AI chatbots.
Graduate Research: Excellence in Research & Teaching This training will provide an introduction to data linkage for students and researchers involved in data linkage research. Students will be ...
The MSR Ability team’s mission is to empower people with disabilities (long-term, temporary, or situational). We conduct user-focused research to invent novel, accessible technologies that combine ...
OPTIMAL is a NHMRC-funded Centre of Research Excellence in OPTimising Immunoglobulin Management in Australia. Bringing together patients, leading researchers, health professionals and health ...
The performance of deep convolution neural networks will be further enhanced with the expansion of the training data set. For the image classification tasks, it is necessary to expand the insufficient ...
Find more information about Crossref citation counts. The Altmetric Attention Score is a quantitative measure of the attention that a research article has received online. Clicking on the donut icon ...
Common Data Set The Common Data Set (CDS) initiative is a collaborative effort among institutional researchers and guidebook publishers, as represented by the College Board, Peterson's, and U.S. News ...
How should we think about the use of student data by colleges and universities in efforts to improve student retention or academic success?
The Trade Desk on Thursday announced its first native app built for use with a separate cloud or data warehouse. It’s called the Connector App on Snowflake. The idea is to more readily connect sales ...
Classically, machine learning methods are evaluated according to their accuracy and model size. Increasingly model parameters are used to interpret the model in order to extract information about the ...