Results 21 to 30 of about 6,974,166 (301)
Computer generated volume holograms fabricated on a coreless fiber tip by two photon polymerization [PDF]
EPJ Web of ConferencesComputer-generated volume holograms (CGVHs) contain 3D refractive index modulations designed to create complex-shaped wave fields for various optical applications.
Jalili Mansoureh +3 more
doaj +1 more source
PSYCHOPHYSICS OF REMEMBERING: TO BIAS OR NOT TO BIAS? [PDF]
Journal of the Experimental Analysis of Behavior, 2010 Delayed matching to sample is typically a two‐alternative forced‐choice procedure with two sample stimuli. In this task the effects of varying the probability of reinforcers for correct choices and the resulting receiver operating characteristic are symmetrical.
K Geoffrey, White, John T, Wixted
openaire +2 more sources
Salmon: fast and bias-aware quantification of transcript expression using dual-phase inference
Nature Methods, 2017 We introduce Salmon, a lightweight method for quantifying transcript abundance from RNA–seq reads. Salmon combines a new dual-phase parallel inference algorithm and feature-rich bias models with an ultra-fast read mapping procedure.
Rob Patro +4 more
semanticscholar +1 more source
Qualifying parabolic mirrors with deflectometry [PDF]
Journal of the European Optical Society-Rapid Publications, 2013 Phase-measuring deflectometry is a full-field gradient technique that lends itself very well to testing reflective optical surfaces. In the past, the industry’s interest has been focussed mainly on the detection of defects and ripples, since it is easy ...
Burke J. +4 more
doaj +1 more source
Applied Sciences, 2021 Optical metrology is a key element for many areas of modern production. Preferably, measurements should take place within the production line (in-process) and keep pace with production speed, even if the parts have a complex geometry or are difficult to ...
Ralf B. Bergmann +2 more
doaj +1 more source
ROBINS-I: a tool for assessing risk of bias in non-randomised studies of interventions
British medical journal, 2016 Non-randomised studies of the effects of interventions are critical to many areas of healthcare evaluation, but their results may be biased. It is therefore important to understand and appraise their strengths and weaknesses. We developed ROBINS-I (“Risk
J. Sterne +34 more
semanticscholar +1 more source
StereoSet: Measuring stereotypical bias in pretrained language models [PDF]
Annual Meeting of the Association for Computational Linguistics, 2020 A stereotype is an over-generalized belief about a particular group of people, e.g., Asians are good at math or African Americans are athletic. Such beliefs (biases) are known to hurt target groups.
Moin Nadeem, Anna Bethke, Siva Reddy
semanticscholar +1 more source
BBQ: A hand-built bias benchmark for question answering [PDF]
Findings, 2021 It is well documented that NLP models learn social biases, but little work has been done on how these biases manifest in model outputs for applied tasks like question answering (QA).
Alicia Parrish +7 more
semanticscholar +1 more source
More human than human: measuring ChatGPT political bias
Public Choice, 2023 We investigate the political bias of a large language model (LLM), ChatGPT, which has become popular for retrieving factual information and generating content.
Fabio Motoki +2 more
semanticscholar +1 more source
Catalogue of bias: publication bias [PDF]
BMJ Evidence-Based Medicine, 2018 Dickersin and Min define publication bias as the failure to publish the results of a study ‘on the basis of the direction or strength of the study findings’.1 This non-publication introduces a bias which impacts the ability to accurately synthesise and describe the evidence in a given area.2 Publication bias is a type of reporting bias and closely ...
Nicholas J DeVito, Ben Goldacre
openaire +2 more sources