“…In Study 2, we found that a simple accuracy reminder at the beginning of the study (i.e., judging the accuracy of a non-COVID-19-related headline) nearly tripled the level of truth discernment in participants’ subsequent sharing intentions. …”
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“…The essential training and validation datasets with high-quality 3D ground-truth labels are prepared by using a multi-frequency fringe projection profilometry technique. …”
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“…Furthermore, to assess performance on empirical data where the ground truth is unknown, we introduce a phylogeny-based measure for identifying potentially erroneous inferences. …”
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“…In our proposed method, the slices from an MRI scan are divided into non-overlapping patches that are fed into the U-net model along with their corresponding patches of ground truth so as to train the network. The experimental results show that the proposed patch-wise U-net model achieves a Dice similarity coefficient (DSC) score of 0.93 in average and outperforms the conventional U-net and the SegNet-based methods by 3% and 10%, respectively, for on Open Access Series of Imaging Studies (OASIS) and Internet Brain Segmentation Repository (IBSR) dataset.…”
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“…The outcomes of this approach were compared with manually obtained FTA measurements from the OAI dataset as the ground truth. Based on experiments, the difference in measurement results between the FTA of the OAI and the FTA obtained using our method is quite small, i.e., below 0.81° for the right FTA and below 0.77° for the left FTA with minimal average errors. …”
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“…The dataset is released with a ground truth annotation reporting the exact time intervals during which volunteers actually interacted. …”
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“…One of the most concerning notions for science communicators, fact-checkers, and advocates of truth, is the backfire effect; this is when a correction leads to an individual increasing their belief in the very misconception the correction is aiming to rectify. …”
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“…Annotations of the videos provided the “ground-truth” for FOG detection. A leave-one-patient-out validation process with a training set of 57 subjects resulted in 84.1% sensitivity, 83.4% specificity, and 85.0% accuracy for FOG detection. …”
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“…In the logical rule training stage, the dynamic trend states of up and down are mapped to the two dimensions of truth-membership and false-membership of neutrosophic sets, respectively. …”
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“…However, these approaches typically require a large amount of ground truth training data in the form of image annotations made by human experts. …”
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“…Participants (N = 99) were instructed to lie or tell the truth about their attitudes. We obtained the same results as Johnson et al. (2008): lies were accompanied by enhanced medial frontal negativities (MFN) and suppressed late positive components (LPCs) indicating that lying relied on stronger cognitive control processes and response conflicts than being honest. …”
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“…We propose in this article, after having shown how much RLSS stems from a myth and not from a scientific approach, to expose its origins and genesis, essential to the understanding of its current character of so-called incontestable truth, then to illustrate the worrying practical and epistemological consequences that this reference to RLSS entails. …”
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“…First, a large dataset was recorded from a number of participants performing isometric contractions in different postures, while simultaneously recording HD-EMG channels and ground-truth force. The EMG signals were acquired from three linear surface electrode arrays, each with eight monopolar channels, and were placed on the long head and short head of the biceps brachii and brachioradialis. …”
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“…This marks an improvement of 13.22% as compared to ground truth predictions obtained from labeling insensitive towards non-manual content. …”
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“…We contribute a study with 29 subjects wearing running shoes equipped with four IMUs on both the left and the right shoes and a motion capture system as ground truth. The results show that the IMUs measure different raw data depending on their position on the foot and that the accuracy of the spatio-temporal parameters depends on the sensor position. …”
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“…In our field experiment, where ground truth was unavailable, the sources estimated to be inactive based on the complete set of measurements were found inactive (up to three decimal places of accuracy) at least 72% of the time even when estimated using just 54% of random measurements. …”
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“…Its classification accuracy on ground truth data reached >95% outperforming human operators and commonly used threshold, only requiring ~1% of the time. …”
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“…Players are told they must decide how many virtual coins they want to input into a virtual black box that will provide uncertain returns. However, in truth, they are playing with each other in a repeated social game. …”
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“…Though synthetic images by the U-Net method has less contrast information than those by the CycleGAN method, the pixel value profile tendency of the synthetic images by the U-Net method is closer to the ground truth images. This work demonstrated that supervised deep learning method outperforms unsupervised deep learning method in accuracy for medical tasks of MR/CT synthesis.…”
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“…We also observed that the default imputation methods from MICE showed a significant increase in FI relative to the ground truth together with a decrease in predictive power, hence we suggest other options when performing imputation with NHANES. …”
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