True positive rate
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Evaluating the replicability of social science experiments in Nature and Science between 2010 and 2015 Open
Being able to replicate scientific findings is crucial for scientific progress1-15. We replicate 21 systematically selected experimental studies in the social sciences published in Nature and Science between 2010 and 201516-36. The replica…
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Reduced False Positives and Improved Reporting of Loop-Mediated Isothermal Amplification using Quenched Fluorescent Primers Open
Loop-mediated isothermal amplification (LAMP) is increasingly used in molecular diagnostics as an alternative to PCR based methods. There are numerous reported techniques to detect the LAMP amplification including turbidity, bioluminescenc…
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Evaluating the replicability of social science experiments in Nature and Science between 2010 and 2015 Open
Being able to replicate scientific findings is crucial for scientific progress. We replicate 21 systematically selected experimental studies in the social sciences published in Nature and Science between 2010 and 2015. The replications fol…
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Reducing false positives in fraud detection: Combining the red flag approach with process mining Open
Fraud detection often includes analyzing large datasets of enterprise resource planning systems to locate irregularities. Analysis of the datasets often results in a large number of false positives, that is, entries wrongly identified as f…
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Real-time detection of colon polyps during colonoscopy using deep learning: systematic validation with four independent datasets Open
We developed and validated a deep-learning algorithm for polyp detection. We used a YOLOv2 to develop the algorithm for automatic polyp detection on 8,075 images (503 polyps). We validated the algorithm using three datasets: A: 1,338 image…
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The Effectiveness of Software Designed to Detect AI-Generated Writing: A Comparison of 16 AI Text Detectors Open
This study evaluates the accuracy of 16 publicly available AI text detectors in discriminating between AI-generated and human-generated writing. The evaluated documents include 42 undergraduate essays generated by ChatGPT-3.5, 42 generated…
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Dataset decay and the problem of sequential analyses on open datasets Open
Open data allows researchers to explore pre-existing datasets in new ways. However, if many researchers reuse the same dataset, multiple statistical testing may increase false positives. Here we demonstrate that sequential hypothesis testi…
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Real-time polyp detection model using convolutional neural networks Open
Colorectal cancer is a major health problem, where advances towards computer-aided diagnosis (CAD) systems to assist the endoscopist can be a promising path to improvement. Here, a deep learning model for real-time polyp detection based on…
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Dual-reporter SERS-based biomolecular assay with reduced false-positive signals Open
Significance Whereas new biomolecular assays are continually being developed to achieve higher detection sensitivities, specificity is often the primary factor limiting an assay’s detection threshold—especially in single-label/signal ampli…
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Ear Detection under Uncontrolled Conditions with Multiple Scale Faster Region-Based Convolutional Neural Networks Open
Ear detection is an important step in ear recognition approaches. Most existing ear detection techniques are based on manually designing features or shallow learning algorithms. However, researchers found that the pose variation, occlusion…
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Newborn Screening for Lysosomal Storage Diseases: Methodologies, Screen Positive Rates, Normalization of Datasets, Second-Tier Tests, and Post-Analysis Tools Open
All of the worldwide newborn screening (NBS) for lysosomal storage diseases (LSDs) is done by measurement of lysosomal enzymatic activities in dried blood spots (DBS). Substrates used for these assays are discussed. While the positive pred…
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Comparing the performance of selected variant callers using synthetic data and genome segmentation Open
Spiking data sets with specific mutations -single-nucleotide variations (SNVs), single-nucleotide polymorphisms (SNPs), or structural variations (SVs) in this study-at known locations in the genome provides an effective and economical way …
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Uncovering a Blind Spot in Sensitive Question Research: False Positives Undermine the Crosswise-Model RRT Open
Validly measuring sensitive issues such as norm violations or stigmatizing traits through self-reports in surveys is often problematic. Special techniques for sensitive questions like the Randomized Response Technique (RRT) and, among its …
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Recovering True Classifier Performance in Positive-Unlabeled Learning Open
A common approach in positive-unlabeled learning is to train a classification model between labeled and unlabeled data. This strategy is in fact known to give an optimal classifier under mild conditions; however, it results in biased empir…
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Detecting and Characterizing Lateral Phishing at Scale Open
We present the first large-scale characterization of lateral phishing attacks, based on a dataset of 113 million employee-sent emails from 92 enterprise organizations. In a lateral phishing attack, adversaries leverage a compromised enterp…
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A method for the identification of COVID-19 biomarkers in human breath using Proton Transfer Reaction Time-of-Flight Mass Spectrometry Open
The results showed that this method for the identification of COVID-19 infection is a promising tool, which can give fast and accurate results.
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Publisher’s note: False positives and false negatives in functional near-infrared spectroscopy: issues, challenges, and the way forward Open
[This corrects the article DOI: 10.1117/1.NPh.3.3.031405.].
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Adaptive Cuckoo Filters Open
We introduce the adaptive cuckoo filter (ACF), a data structure for approximate set membership that extends cuckoo filters by reacting to false positives, removing them for future queries. As an example application, in packet processing qu…
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A robust convolutional neural network for lung nodule detection in the presence of foreign bodies Open
Lung cancer is a major cause of death worldwide. As early detection can improve outcome, regular screening is of great interest, especially for certain risk groups. Besides low-dose computed tomography, chest X-ray is a potential option fo…
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Assisting Static Analysis with Large Language Models: A ChatGPT Experiment Open
Recent advances of Large Language Models (LLMs), e.g., ChatGPT, exhibited strong capabilities of comprehending and responding to questions across a variety of domains. Surprisingly, ChatGPT even possesses a strong understanding of program …
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dearseq: a variance component score test for RNA-seq differential analysis that effectively controls the false discovery rate Open
RNA-seq studies are growing in size and popularity. We provide evidence that the most commonly used methods for differential expression analysis (DEA) may yield too many false positive results in some situations. We present dearseq, a new …
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Machine Learning-Enabled Pipeline for Large-Scale Virtual Drug Screening Open
Virtual screening is receiving renewed attention in drug discovery, but progress is hampered by challenges on two fronts: handling the ever-increasing sizes of libraries of drug-like compounds and separating true positives from false posit…
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Automatic mouse ultrasound detector (A-MUD): A new tool for processing rodent vocalizations Open
House mice (Mus musculus) emit complex ultrasonic vocalizations (USVs) during social and sexual interactions, which have features similar to bird song (i.e., they are composed of several different types of syllables, uttered in succession …
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FDHE-IW: A Fast Approach for Detecting High-Order Epistasis in Genome-Wide Case-Control Studies Open
Detecting high-order epistasis in genome-wide association studies (GWASs) is of importance when characterizing complex human diseases. However, the enormous numbers of possible single-nucleotide polymorphism (SNP) combinations and the dive…
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Adaptive Cuckoo Filters Open
We introduce the adaptive cuckoo filter (ACF), a data structure for approximate set membership that extends cuckoo filters by reacting to false positives, removing them for future queries. As an example application, in packet processing qu…
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Learning to reduce false positives in analytic bug detectors Open
Due to increasingly complex software design and rapid iterative development, code defects and security vulnerabilities are prevalent in modern software. In response, programmers rely on static analysis tools to regularly scan their codebas…
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On-farm detection of claw lesions in dairy cows based on acoustic analyses and machine learning Open
Claw lesions are a serious problem on dairy farms, affecting both the health and welfare of the cow. Automated detection of lameness with a practical, on-farm application would support the early detection and treatment of lame cows, potent…
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High‐Precision Viral Detection Using Electrochemical Kinetic Profiling of Aptamer‐Antigen Recognition in Clinical Samples and Machine Learning Open
High‐precision viral detection at point of need with clinical samples plays a pivotal role in the diagnosis of infectious diseases and the control of a global pandemic. However, the complexity of clinical samples that often contain very lo…
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A novel bi-anomaly-based intrusion detection system approach for industry 4.0 Open
International audience
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Does it matter for the radiologists’ performance whether they read short or long batches in organized mammographic screening? Open
Objective To analyze the association between radiologists’ performance and image position within a batch in screen reading of mammograms in Norway. Method We described true and false positives and true and false negatives by groups of imag…